U.S. patent application number 10/610157 was filed with the patent office on 2004-06-03 for intelligent electro-optical sensor array and method for analyte detection.
This patent application is currently assigned to Trustees of Tufts College. Invention is credited to Kauer, John S., White, Joel E..
Application Number | 20040106211 10/610157 |
Document ID | / |
Family ID | 29420732 |
Filed Date | 2004-06-03 |
United States Patent
Application |
20040106211 |
Kind Code |
A1 |
Kauer, John S. ; et
al. |
June 3, 2004 |
Intelligent electro-optical sensor array and method for analyte
detection
Abstract
The invention relates to a chemical sensor, sensing system and
sensing method which provides for a multi-sensor, cross-reactive,
sensor array having a rapid response time, dynamic modulation of
sampling parameters, and real-time feedback control of sampling and
detection conditions. The device and method provide for smart
detection and discrimination of analytes in fluids through
intelligent sampling, detection, and control algorithms. The
invention further provides for a sensor array having discrete
sensor elements dispersed on fluid-permeable, high surface area,
porous, textured substrates. The innovative device and method
exhibit high sensitivity, discrimination and detection capability
for target analytes at ppb and sub ppm concentrations.
Inventors: |
Kauer, John S.; (Weston,
MA) ; White, Joel E.; (Millis, MA) |
Correspondence
Address: |
NIXON PEABODY LLP
101 FEDERAL ST
BOSTON
MA
02110
US
|
Assignee: |
Trustees of Tufts College
Medford
MA
|
Family ID: |
29420732 |
Appl. No.: |
10/610157 |
Filed: |
June 30, 2003 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10610157 |
Jun 30, 2003 |
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09507210 |
Feb 18, 2000 |
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6649416 |
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Current U.S.
Class: |
436/169 ;
422/400; 422/82.05; 422/82.08; 436/172 |
Current CPC
Class: |
G01N 21/85 20130101;
G01N 21/645 20130101; G01N 2021/7786 20130101; G01N 21/6428
20130101 |
Class at
Publication: |
436/169 ;
436/172; 422/082.05; 422/082.08; 422/058 |
International
Class: |
G01N 021/64 |
Goverment Interests
[0001] The invention described herein was supported in part with
U.S. Government funding under Defense Advanced Research Projects
Agency Contract No. DAAK60-97-K-9502, Office of Naval Research
Grant No. 00014-95-1-1340, National Institutes of Health Grant No.
R01-DC00228. The U.S. Government has certain rights to this
invention.
Claims
What is claimed is:
1. An optical sensor for detecting target analytes in a fluid, said
sensor comprising: a fluid-permeable, textured dye substrate having
a high surface area and high surface area to volume ratio, said
substrate having high open porosity, said substrate having high
permeability to fluids; and a dye compound dispersed on a plurality
of internal and external surfaces within said textured dye
substrate, said dye compound providing a characteristic optical
response when subjected to excitation light energy in the presence
of said target analytes.
2. The sensor of claim 1 wherein said dye substrate is comprised of
a fibrous material.
3. The sensor of claim 2 wherein said fibrous material is selected
from the group consisting of papers, tissues, textiles, woven
fabrics, felts, fibers, fiber bundles, composites, and laminates of
the same.
4. The sensor of claim 1 wherein said dye substrate is comprised of
a particulate material.
5. The sensor of claim 4 wherein said particulate is selected from
the group consisting of glasses, silicas, aluminas, ceramics,
polymers, plastics, metals composites, sintered powders, and
fritted assemblages of the same.
6. The sensor of claim 1 wherein said dye compound comprises a
fluorescent dye.
7. The sensor of claim 6 wherein said dye compound further
comprises a polymer.
8. The sensor of claim 6 wherein said dye fluorescent dye is a
solvatochromic dye.
9. The sensor of claim 8 wherein said solvatochromic dye is
selected from the group consisting of Nile Red, Prodan,
6-propionyl-2-(N,N-dimethylamin- o) napthalene, Acrylodan, and
6-acryloyl(dimethylamino) napthalene.
10. A sensor array for detecting target analytes in a fluid, said
sensor array comprising: a plurality of fluid-permeable, textured
dye substrates having a high surface area and high surface area to
volume ratio, said substrates having high open porosity, said
substrates having high permeability to fluids; a plurality of dye
compounds dispersed on a plurality of internal and external
surfaces within said textured dye substrates, said dye compounds
providing a characteristic optical response when subjected to
excitation light energy in the presence of a target analyte; said
dye substrates and said dye compounds forming a plurality of sensor
array elements; and a substrate support.
11. The sensor array of claim 10 wherein said dye substrates are
comprised of a fibrous material.
12. The sensor of claim 11 wherein said fibrous material is
selected from the group consisting of papers, tissues, textiles,
woven fabrics, felts, fibers, fiber bundles, composites, and
laminates of the same.
13. The sensor of claim 10 wherein said dye substrates are
comprised of a particulate material.
14. The sensor of claim 13 wherein said particulate is selected
from the group consisting of glasses, silicas, aluminas, ceramics,
polymers, plastics, metals composites, sintered powders, and
fritted assemblages of the same.
15. The sensor of claim 10 wherein said dye compounds comprise a
fluorescent dye.
16. The sensor of claim 15 wherein said dye compounds further
comprise a polymer.
17. The sensor of claim 15 wherein said fluorescent dye is a
solvatochromic dye. selected from the group consisting of Nile Red,
Prodan, 6-propionyl-2-(N,N-dimethylamino)napthalene, Acrylodan, and
6-acryloyl(dimethylamino) napthalene.
18. A sensor array according to claim 10 further comprising an
excitation light energy source in optical communication with said
sensor array elements.
19. A sensor array according to claim 11 further comprising an
emission light energy detection means in optical communication with
said sensor array elements.
20. A method for detecting a target analyte in a fluid comprising
the steps of: a) contacting said sample with a sensor array
comprising: i) a fluid-permeable, textured dye substrate having a
high surface area and high. surface area to volume ratio, said
substrate having high open porosity, said substrate having high
permeability to fluids; and ii) a dye compound dispersed on a
plurality of internal and external surfaces within said textured
dye substrate, said dye compound providing a characteristic optical
response when subjected to excitation light energy in the presence
of a target analyte; and b) detecting the presence or absence of
said target analyte.
21. The method of claim 20 wherein said contacting further
comprises drawing said fluid into a sample chamber and exposing
said array to said fluid for no more than five seconds.
22. The method of claim 20 wherein said detecting further
comprises: illuminating said sensor with excitation light energy;
and measuring an optical response produced by said sensor due to
the presence of said analyte with a detector means.
23. The method of claim 22 further comprising identifying said
analyte by employing a pattern-matching algorithm; and comparing
said optical response of said sensor with said characteristic
optical response.
24. The method of claim 22 further comprising identifying said
analyte by providing spatio-temporal response patterns of said
optical response; and recognizing said patterns through a method
selected from the group consisting of a template matching, neural
networks, delay line neural networks, or statistical analysis.
25. A method for detecting a target analyte in a fluid comprising
the steps of: setting primary sampling parameters for a sensor
array; contacting said fluid with said array; detecting a first
plurality of optical responses produced by interaction of said
fluid with said array; comparing said first plurality of responses
to a first stored spatio-temporal response for said primary
parameters for said analyte; setting secondary sampling parameters
for said array wherein at least one sampling parameter is changed;
detecting a second plurality of optical responses produced by
interaction of said fluid with said array; comparing said second
plurality of responses to a second stored spatio-temporal response
for said secondary parameters for said analyte; and detecting the
presence or absence of said analyte.
26. The method of claim 25 wherein said setting primary sampling
parameters comprises: adjusting an excitation light source to a
non-zero minimum intensity; setting a fluid sampling time to a
non-zero minimum time; adjusting said fluid flow to a non-zero
minimum flow rate; and setting a number of sampling time points to
a non-zero minimum. setting a number of sniff samples to a
maximum
27. The method of claim 25 wherein said setting secondary sampling
parameters comprises: incrementing said number of sniff samples by
at least one; selecting said at least one parameter setting from
the group consisting of amplifier gain, fluid sampling time, fluid
flow rate, number of sampling time points, sample sniff rate,
amplifier high pass filtering, excitation light source intensity,
and exhale velocity; and modifying said at least one parameter
setting from an initial setting value.
28. A sensing system for detecting and identifying an analyte in a
fluid comprising: a cross-reactive sensor array comprising a
plurality of dye compounds, a plurality of porous, permeable, high
surface area, textured dye substrates, said dye compounds and said
dye substrates forming a plurality of sensor elements, a substrate
support; an excitation light source array comprising a plurality of
light sources optically coupled to said sensor elements; a detector
array comprising a plurality of detectors optically coupled to said
sensor elements; a sample chamber for housing said sensor elements,
said light source array, said detector array; a sampling means
enclosed in said chamber for drawing said fluid into said chamber
for contact with said sensor array for a controlled exposure time;
a controller means in electrical communication with said light
sources, said detectors, and said sampling means, said controller
means electrically coordinating and switching said sampling means
with said light sources and said detectors for sampling said fluid,
measuring optical responses of said array sensors to said fluid,
and detecting said analyte; and an analyte identification algorithm
for comparing said measured sensor optical responses to
characteristic optical responses of said sensors to target analytes
and identifying said analyte in said fluid.
29. A smart sensing system for intelligent detecting and
identifying an analyte in a fluid comprising: a cross-reactive
sensor array comprising a plurality of sensors; a detector array
comprising a plurality of detectors in communication with said
sensors; a sampling chamber for housing said sensor array and said
detector array; a sampling means enclosed in said chamber for
drawing said fluid into said chamber for contact with said sensor
array for a controlled exposure time; a microcontroller in
electrical communication with said sampling means and said detector
array, said controller means electrically coordinating and
switching said sampling means and said detector array for sampling
said fluid, measuring responses of said sensors to said fluid,
detecting said analyte, and reporting an analyte detection result;
an intelligent sampling algorithm for directing said
microcontroller, said sampling algorithm selecting sensors and
detectors, said sampling algorithm coordinating said electrical
communication for said switching, said sampling, said measuring,
said detecting and said reporting, said sampling algorithm setting
first and second sampling parameters; and an analyte identification
algorithm in communication with said sampling algorithm and said
microcontroller, said identification algorithm comparing said
measured sensor optical responses to characteristic responses of
said sensors to target analytes and identifying said analyte in
said fluid.
30. The sensing system of claim 29 wherein said identification
algorithm comprises a response report comparing a spatio-temporal
pattern of said measured optical responses to a spatio-temporal
pattern of said characteristic responses; and an identification
report selected from the group consisting of a pattern match, a
delay line neural network match, and a neuronal network match.
Description
FIELD OF THE INVENTION
[0002] This invention generally relates to sensors and methods for
detecting analytes. More particularly, this invention relates to
optical sensors, sensor arrays, sensing systems and sensing methods
for intelligent sensing and detection of unknown materials by way
of real-time feedback and control of sampling conditions.
BACKGROUND OF THE INVENTION
[0003] U.S. Pat. No. 4,859,864 to Smith discloses an air bubble
sensor that employs light emitting diode (LED) light sources,
phototransistor detectors, and displays or alarms for detecting the
presence of bubbles in a fluid sample.
[0004] U.S. Pat. No. 5,674,751 to Jaduszliwer, et al. disclose a
hydrazine fuel fiber optic sensor that employs a diode laser pulsed
light source, a calorimetric fiber optic sensor system, and a
photodetector to detect changes in spectral absorption due to ppb
levels of hydrazine fuel.
[0005] U.S. Pat. No. 5,445,795 to Lancaster, et al. disclose a
portable optical sensor for detecting volatile organic compounds
(VOCs) in vapors and aqueous media. The disclosed device comprises
a vapochromic sensor formed from transition metal complex salts, a
sensor chamber, a vacuum pump for drawing samples into the chamber,
a light source for illuminating the sensor, a light detector
responsive to light reflected from the vapochromic sensor, and a
detection means for determining a color change in the sensor due to
the presence of VOCs. In one disclosed embodiment for fuel tank
sensing, the sensor, an LED illuminating light source, and a
photodiode detector with an optical band-pass filter are all housed
within the sensor chamber and a photodiode feedback signal is
provided to a control means for adjusting a fuel metering valve via
signal processing electronic circuitry. Other embodiments employ a
bi-color LED that can be modulated between two wavelengths and
gated detection electronics in the detector is synchronized with
LED driver current to monitor small changes in reflected signals at
both wavelengths.
[0006] U.S. Patent No. 5,116,759 to Klainer, et al. discloses a
vapor or liquid chemical sensor where analytes pass into a sampling
cell where they contact sensing solutions for detection. The
disclosed device comprises a single illumination source, an
optional semi-permeable analyte membrane, a chamber with one or
more analyte-sensitive solutions contained in a reservoir cell, a
sample signal detector for detecting optical changes in the cell
due to the analyte, and an optional reference signal detector for
background signal correction. Reagent and sampling pumps are also
disclosed for continuously flushing the cell with analyte and
solution reagent. The disclosed device employs diodes, lasers or
lamps as an excitation source, optically responsive analyte sensing
solutions, detectors, and conventional electronic circuitry that
are known in the art. In a preferred embodiment, an LED is the
preferred light source and a photodiode is the preferred detector.
Other embodiments disclose a light source sensor, a source
stabilizer, a detector stabilizer, and a temperature sensor and
compensator circuitry for feedback, monitoring and stabilizing the
light source and detector. Disclosed embodiments include an A/D
interface, alarms, display, recorders or plotters for readout, a
computer and software.
[0007] Persaud and Dodd (Nature v. 299, pp. 352-355, 23 Sep. 1982)
disclose an electronic nose comprised of semi-selective sensors in
a cross-reactive sensor array designed to mimic a mammalian
olfactory system. The disclosed sensors comprise commercially
available semiconductor transducer gas sensors that exhibit a
conductance change when the adsorb ambient vapors. The disclosed
sensors were capable of detecting vapors at high concentrations
ranging from 0,1 to 10 mols per liter of air. The response time for
these sensors ranged from 1 to 3 minutes. Measurements made with
various sensor parings demonstrated selectivity toward a number of
analyte vapors at high concentrations.
[0008] U.S. Pat. No. 5,512,490 to Walt and Kauer disclose a fiber
optic sensor with semi-selective sensors in a cross-reactive sensor
array that employs spectral recognition patterns for identifying
and detecting a variety of analytes. The reference teaches thin
film sensors formulated by mixing polymers with dye compounds. The
sensors are immobilized on either a solid planar translucent or
transparent substrate or a fiber optic fiber or bundle. In a
preferred embodiment, the substrate is a transparent optical fiber
bindle in which sensors are placed on the ends of optical fibers or
groups of such fibers. The sensing system taught by this reference
utilizes an arc lamp excitation source, an optical train comprising
a series of lenses, filters which are sequentially switched to
provide for changes in both excitation light wavelength and emitted
light wavelength, and a CCD camera detector which captures spatial
images of the fluorescence intensity of individual sensor elements
at various wavelengths. The measured responses of individual
sensors to analytes are combined to form a pattern of spectral
responses over time that are unique to a specific analyte. Spectral
response patterns are stored in a library and the response patterns
generated from unknown samples are compared with library patterns
to identify and detect target analytes. Either light intensity or
wavelength may be employed for analyte determinations
[0009] U.S. Pat. No. 5,063,164 to Goldstein discloses a biomimetic
sensor for detecting airborne toxins. The disclosed device
comprises a porous, semi-transparent substrate which is
sufficiently transmissive to light to permit detection of
transmitted light by an LED and photodiode and is impregnated with
a self-regenerating sensor. The sensor allegedly mimics the human
response to toxins with regard to sensitivity and affinity by
employing a molecular encapsulant that contains a chemical sensor
reagent. The disclosed device provides for detecting a change in
optical density of the sensor which is dependent on toxin
concentration and time of exposure. For dilute analyte levels,
extended exposure times are required for adequate sensitivity and
detection.
[0010] Smardzewski [Talanta 35(2):95-101(1988)] discloses a
multi-element optical waveguide sensor for detecting analytes in
fluids which comprises eight fiber optic waveguides each
circumferentially coated with sensing material, an array of eight
sequentially-activated LEDs optically coupled to the waveguide
assembly, and a single detector or array of multiple detectors,
photomultiplier tubes or photodiodes, optically coupled to the
waveguide assembly. Samples are passed over the outer surface of
the coated waveguides and color changes produced by analyte
interaction with the coating are monitored. In the disclosed
method, each channel is sampled sequentially with measurements made
on a single channel before moving to a subsequent channel. In the
disclosed method the LEDs are pulsed on and off with switching
times of at least one millisecond during measurements. The device
provides for sensor signal output to be visually displayed or input
to a microprocessor pattern-recognition algorithm. CMOS analog
switches/multiplexers are used in feedback loops to control
automatic gain-ranging, light-level adjustment and
channel-sequencing. The detection limit and sensitivity of the
disclosed device and method are limited to ppm levels.
[0011] Kopola, et al. [SPIE, Fiber Optic Sensors, v. 586, pp.
204-210 (1985)] disclose an eight channel spectrophotometer for
measuring spectral reflectance at discrete wavelengths. The
disclosed device comprises eight different LED light sources that
cover a wavelength range between 480 nm and 1500 nm, a reference
and measurement photodiode detector, a temperature controller, a
fiber optic probe, signal conditioning electronics, microprocessor
controller, and a display and plotter interface. In the disclosed
method, measurements of both a reference LED output signal and
sample LED output signal, which is modulated by the presence of an
analyte, are simultaneously made with a single LED source and each
reference and measurement detectors. With the disclosed device and
method, sample measurements are time multiplexed with measurements
made sequentially for each individual LED channel.
[0012] Hauser, et al. [Meas.Sci.Technol. 6:1082-1085(1995)]
disclose a chemical sensor comprising LED light sources and
filtered sample and reference photodiode detectors coupled to a
fiber optic for detecting the optical response of a sensing
membrane to analytes. The LED is modulated at 2 kHz. The disclosed
device provides for a light demodulator for background signal
corrections. Detector and reference signals are ratioed to
compensate for instability in the LED light source. The sensitivity
of the disclosed device and method apparently is limited to 0.2% or
2000 ppm detection limits. Disclosed sampling times of several
minutes or more are apparently required.
[0013] Bruno, et al. [Anal. Chem. 69(3):507-513(1997)] disclose a
six channel sensor array for detecting blood analytes. The
disclosed device comprises LED light sources, excitation and
emission filters, photodiode detectors, pH membrane sensors and
electronic circuitry. The device provides for modulating LED
driving current and photodiode gain factors and providing output to
a computer via an A/D/ converter for display and analysis of data
and control of fluid flow to the sensor. The disclosed sensor
response time is approximately 30 seconds with a sampling time
ranging from 1 to 15 minutes for each sensor. Sensitivity of the
device is limited by signal noise caused by temperature and
pressure variations due to sample fluid flowing through the sensor
cell. An additional limitation with the disclosed device and method
is a diminished responsivity of sensors with extended light
exposure during sampling due to photobleaching.
[0014] Holobar, et al. [Anal.Methods and Instrum.
2(2):92-100(1995)] disclose a double-beam, flow-through pH sensor
that employs a sample solution pump, an LED light source and two
filtered photodiodes, one as a reference detector and the other as
a sample detector. The disclosed sensor response time is
approximately 20-30 seconds.
[0015] Boisde, et al. [Chemical and Biochemical Sensing with
Optical Fibers and Waveguides, Artech House (Boston, 1996)] have
reviewed the state of fiber optic chemical sensor art and have
shown that LED excitation light sources, photodiode detectors, and
multi-channel sensor wavelength multiplexing and spatial
multiplexing are known in the art.
[0016] Taib, et al. [Analyst 120(6):1617-1625(1995)] have reviewed
solid-state fiber optic sensor instrumentation and have shown that
LED light sources, fiber optic light guides, optical transducers
for analyte detection, amplifiers, signal processors and output
devices are all known in the art of chemical sensor technology. The
authors note that LEDs are particularly amenable to high frequency
electronic modulation, that the response time of photodiode
detectors was in the microsecond range, and that the use of
multiple sensor channels with filtered LEDs and photodiodes and
microprocessor control of pulsed of LED sources can provide
advantageous simultaneous multi-channel/multi-parameter
measurements. The authors additionally note that multi-channel
sensors may be coupled to microprocessors to carry out parallel
signal processing under software control and thereby exploit the
capabilities of pattern recognition and artificial neural network
methods.
[0017] Despite the many advantageous features provided by current
chemical sensor technology, there is a need for a chemical sensor,
sensing system and sensing method which provide for a multi-sensor,
cross-reactive, sensor array having a rapid response time, a rapid
sampling time, dynamic modulation of sampling and detection
parameters, intelligent feedback control of analyte sampling
conditions, smart mode sampling, smart detection through
application of sophisticated analyte detection algorithms, and high
sensitivity, discrimination, and detection capability for a variety
of target analytes at sub ppm to ppb level concentrations.
SUMMARY OF THE INVENTION
[0018] The present invention relates to a chemical sensor, sensing
system and sensing and identification method which provide for a
multi-sensor, cross-reactive, sensor array having a rapid response
time, a rapid sampling time, dynamic modulation of sampling and
detection parameters, intelligent feedback control of analyte
sampling conditions, smart mode sampling, smart detection through
application of sophisticated analyte detection algorithms, and high
sensitivity, discrimination, and detection capability for a variety
of target analytes at sub ppm to ppb level concentrations.
[0019] One object of the present invention is to provide a
relatively inexpensive, robust, dynamically configurable, portable
sensing device.
[0020] An additional object of the present invention is to provide
for porous or fibrous sensor substrates which enhance the
responsivity, selectivity, and discrimination of sensors for target
analytes.
[0021] A further object of the present invention is to provide for
real-time, dynamic configuration of sensor excitation sources,
detectors, sampling time and sampling rate to optimize sensor
responsivity and selectivity for target analytes in a given
sampling environment.
[0022] A yet further object of the present invention is to provide
for rapid sensor response and rapid detection of low level signals
for monitoring sensor temporal response profiles in detecting and
discriminating target analytes.
[0023] A still further object of the present invention is to
provide for an intelligent or "smart" nose that mimics the highly
sensitive and discriminating vapor detection capability of
olfactory systems of animals
[0024] An additional object of the present invention is to enable
sampling under both negative and positive ambient pressure
conditions.
[0025] A further object of the present invention is to provide for
intelligent sensing of target analytes through electronic
modulation of sampling conditions, such as flow rate, sampling
duration, and sensor temporal response profiles by way of
computer-controlled feedback.
[0026] An additional object of the present invention is to provide
for removable, interchangeable sensor array substrates for rapidly
changing sensor materials and sensor sites in the arrays for either
targeting specific analytes or replacing spent sensors when they
lose their responsivity to analytes due to either photo-bleaching
or chemical reaction.
[0027] A further object of the present invention provides for
utilization of a wide variety of sensor materials, such as dyes,
dye-polymers, and polymers conjugated with dyes, which would
normally be considered less suitable with conventional sensing
devices due to relatively small analyte response signals.
[0028] An additional object of the present invention provides for
multiple, cross-reactive sensors deployed in a sensor array for
detecting and discriminating a wide variety of target analytes in
complex sample mixtures.
[0029] Yet another object of the present invention is in providing
directly illuminated sensors that do not require epi-illuminating
optics which produce undesirable optical signal losses at low
response levels.
[0030] A further object of the present invention is in providing
real-time response signal baseline resetting and high gain response
signal amplification tailored to individual sensor elements to
avoid detector saturation, eliminate background fluorescence, and
provide for simultaneous sampling and discrimination with all
sensor elements in the array regardless of relative sensor
responsivity to analytes.
BRIEF DESCRIPTION OF THE DRAWINGS
[0031] This invention is pointed out with particularity in the
appended claims. Other features and benefits of the present
invention can be more clearly understood with reference to the
specification and the accompanying drawings in which:
[0032] FIG. 1 is a schematic diagram comparing a mammalian
olfactory system with the sensing system of the present
invention;
[0033] FIG. 2 is a schematic diagram of the analyte detection
method of the present invention;
[0034] FIG. 3 is a block diagram showing hardware components of the
sensing system of the present invention;
[0035] FIG. 4 is a block diagram of electrical component modules of
the sensing system of the present invention;
[0036] FIG. 5 is a schematic of an electrical circuit of the light
generation module of the present invention;
[0037] FIG. 6a is a schematic diagram of an inhale configuration
for the sample delivery module of the present invention;
[0038] FIG. 6b is a schematic diagram of an exhale configuration
for the sample delivery module of the present invention;
[0039] FIG. 7 is a schematic of an electrical control circuit for
the sample delivery module of the present invention;
[0040] FIG. 8 is a schematic diagram of a sample detection chamber
of the present invention;
[0041] FIG. 9 is a schematic of an electrical circuit of the
preamplifier module of the present invention;
[0042] FIG. 10 is a schematic of an electrical circuit of the
amplifier module of the present invention;
[0043] FIG. 11 is a schematic of the electrical circuit connecting
the channel output lines from the amplifier and input lines of the
A/D converter in the microcontroller computer;
[0044] FIG. 12 is a schematic of an electrical circuit for the
micro-computer control module of the present invention;
[0045] FIGS. 13a-b are schematic diagrams showing a typical sensor
array module configuration for the sensor of the present
invention;
[0046] FIG. 14 is a schematic of a data acquisition timing diagram
used in the sensing method of the present invention;
[0047] FIG. 15 is a schematic flowchart of a sensor training method
employed in the sensing method of the present invention;
[0048] FIG. 16 is a schematic flowchart of an analyte test method
employed in the sensing method of the present invention;
[0049] FIGS. 17a-d show comparative changes in fluorescent sensor
response to methanol, amyl acetate, acetone and dinitrobenzene
analytes with conventional glass sensor substrates and innovative
sensor substrates of the present invention;
[0050] FIG. 18 shows comparative changes in fluorescent sensor
response to saturated DNT explosive analyte with conventional glass
sensor substrates and an innovative sensor substrate of the present
invention;
[0051] FIGS. 19a-b show comparative changes in fluorescent sensor
response to methanol samples at various analyte concentrations with
a conventional glass sensor substrate and an innovative sensor
substrate of the present invention;
[0052] FIG. 20 show time-sensor contour plots of fluorescence
intensity for a nine element sensor array of the present invention
when exposed to various analytes;
[0053] FIG. 21 is a schematic flowchart of the sensor training
method employed in the smart sensing method of Example 3;
[0054] FIG. 22 is a schematic flowchart of the analyte test method
employed in the smart sensing method of Example 3;
[0055] FIGS. 23a-d are plots of sensor fluorescence responses to
acetone and air target analytes with short and long sniffs when
using the smart training method of Example 3;
[0056] FIGS. 24a-e are plots of typical sensor fluorescence
responses of Dow and cellulose-alumina sensors in a fiber optic
sensor array to saturated and unsaturated methanol analyte;
[0057] FIGS. 25a-d are plots of typical sensor fluorescence
responses of a Dow sensor in a fiber optic sensor array to
saturated and unsaturated amyl acetate and xylene; and
[0058] FIGS. 26a-c are plots of typical sensor fluorescence
responses of Dow sensor in the sensor and sensing system of the
present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0059] The conceptual basis of the intelligent sensing device and
method of the present invention has evolved from studies of
biological olfactory systems in which an artificial intelligent
sensing system has been developed which provides for cross-reactive
sensor arrays tailored to address design issues such as how odors
are presented, how the sensing sites are deployed, how the changes
in fluorescence are evaluated over time and space, how the
analytical circuits are designed, how the data are stored and
interpreted, and how pure compounds and mixtures are detected and
identified.
[0060] I. Overview
[0061] FIG. 1 is a schematic diagram comparing a mammalian
olfactory system with the sensing system of the present invention.
In the peripheral olfactory circuit shown at the top of FIG. 1,
many thousands of parallel channels of distributed olfactory
sensory neurons ("Detection/Transduction") in the nasal cavity,
into which odors are drawn by inhalation, extend convergent axonal
projections ("Transmission") to the glomeruli of the olfactory bulb
("Integration"). Periglomerular neurons ("pg") are inhibitory
interneurons that connect the glomerulli with one another and
modulate mitral/tufted neurons ("M/T") cell activity . The M/T have
dendrites extending from the glomeruli to their cell bodies and
give rise to axons that leave the olfactory bulb. Granule neurons
("grl") are inhibitory interneurons that modulate M/T cell
activity.
[0062] The innovative sensing method and sensing device design of
the present invention mimics and parallels the structure and
operational characteristics of the mammalian olfactory system
through the combination of electro-optical hardware component
modules, microprocessor control and software sampling and detection
algorithms. In the artificial nose embodiment shown in FIG. 1, the
sample cavity design mimics the mammalian nasal cavity where odors
(i.e. vapor analytes) are drawn into the sensing module ("sniffed"
or "inhaled") and their interaction with a plurality of sensing
elements ("sensory neurons") in a sensor array triggers an external
event. In one embodiment, the analyte interaction with sensing
elements produces emitted light energy at a detectable
characteristic wavelength when the sensor elements are illuminated
by excitation light energy from a filtered LED array. The
multi-element sensor array of the present invention thus mimics the
sensory neurons of the olfactory system in responding to the
external triggering event, emitted light energy signaling the
presence of an analyte, and detecting this triggering event by way
of a filtered photodiode array ("Detection"). The photodiode
preamplifiers mimic an olfactory sensory neuron by converting the
optical signal to an electrical voltage signal ("Transduction")
which amplified, manipulated and transported via electrical
circuits ("Transmission") to an analog-digital ("A/D") converter
and a software controlled microprocessor for data manipulation,
analysis, feedback control, detection and identification
("Integration"). These features are replicated for each sensor
element in the array. While the embodiment shown in FIG. 1 provides
for 32 array element channels, the present invention provides for
configuring the array with virtually any number of array elements
and channels. Thus, the sensor array of the present invention may
be expanded or contracted without limit by adding or removing
elements and channels according to the requisite analyte detection,
discrimination and identification needs of an specific sampling
application.
[0063] FIG. 2 provides an overview of the analyte sensing and
detection method of the present invention. Ambient odors (analytes)
are sniffed (transported to the sensor array) where the odors
interact with the array sensor elements. Light energy excitation of
the sensor elements in the presence of the odors produces a
detectable optical response signal due to emitted light produced by
analyte interaction with the dyes or dye-polymer compounds in the
sensor elements. The spatio-temporal optical response of the array
to the odor is detected, recorded, manipulated, and then matched to
known target odors via smart analytical algorithms which apply
either pattern matching, neural network, neuronal network, or
statistical analysis methods to detect, discriminate and identify
the odor.
[0064] The hardware and software components and configuration of
the innovative sensor of the present invention provide for an
compact, portable, inexpensive, expandable, rapidly responding
sensing device that can modify its detection strategy on the fly.
The innovative design and method provides for real-time,
on-the-fly, modulation of: a) the output of light emitting diodes
(LEDs), such as wavelength, intensity, and frequency; b) the
detection properties of photodiodes, such as wavelength, gain, and
frequency; c) the sampling parameters, such as frequency, duration,
number, velocity, and rise-fall dynamics; and d) sampling time
constant or temporal filter settings, for dynamically responsive,
smart feedback control in sampling, detection and identification of
analytes.
[0065] In addition to dynamic response modulation, the device and
method further provide for hardware and algorithm implementations
which evaluate the synchrony and noise characteristics across
different sensors, especially those of the same composition being
examined at different wavelengths. This provides a powerful tool
for identifying and utilizing small response signals and rejecting
noise.
[0066] By providing for independently illuminated, detected,
recorded, and modulated sensing channels, levels of flexibility,
expandability, portability, efficiency, and economy are achieved
that are difficult to realize with conventional sensor designs,
light sources, filtering systems, and light detectors. In addition,
the use of small, inexpensive, flexibly programmable, computational
microcomputer platforms and interchangeable sensors and sensor
array modules provides for increased flexibility and tailoring of
sensor performance and capabilities to real world sensing
applications.
I. Sensors
[0067] In the sensing device of the present invention, analytes
(odors) drawn in and out of the sensing chamber are detected by the
fluorescence changes produced by their interaction with sensor
elements during irradiation of the sensors with excitation light in
the presence of the analytes. For optical sensors which rely on
light excitation, absorption and emission, the selection of analyte
detection and discriminating dye indicators is important to the
design and performance characteristics of a cross-reactive sensor
array. An important requirement of candidate dye materials for
optical sensor elements is that they produce a characteristic
optical response signature in the presence of target analytes. The
sensing effect of the dye materials may be based on light
fluorescence, absorption, luminescence, phosphorescence,
electroluminescence, or other methods for modulation of photonic
emission by chemical compounds, such as polymers. These photonic
measures may also be dependent on the physical and chemical
properties of the substrate, or the presence of additional dye
materials.
[0068] Typically, for cross-reactive sensor arrays, it is
preferable to provide sensor array elements formed from dye
materials with different response spectra, different analyte
sensitivities, and different analyte discrimination characteristics
so as to provide broad spectral detection and discrimination for a
variety of analytes. Sensor elements may be comprised of neat dyes,
dye compounds, for example conjugated dyes, or dye-polymer mixtures
which produce characteristic optical responses to analytes of
interest. Sensor materials are generally applied, deposited, or
deployed on substrates in the form of fluids, gels, slurries, thin
or thick film coatings, beads, droplets, spots, protrusions,
fibers, sheets, and other shapes having complex surface textures or
protrusions, including fibrilated or hair-like structures.
A. Dye Materials
[0069] Generally, any dye that provides a detectable characteristic
optical response signature to an analyte at ultraviolet, visible or
infrared wavelengths may be employed. Different dye materials may
require different excitation and emission wavelengths, which can be
accommodated simultaneously in the sensing device of the present
invention by appropriate matching LEDs, photodiodes, and light
filters wavelengths to required dye wavelengths. In a preferred
embodiment, sensors are comprised of a fluorescent dye material
applied to a porous or fibrous substrate material.
[0070] In a preferred embodiment, dye candidate materials which can
be easily applied to and adhere to the innovative fibrous sensor
substrates of the present invention are desired. In alternative
embodiments, where dye-polymer materials are employed, dye
candidates that can be readily incorporated into polymer matrices
and whose optical response characteristics are modified by the
polymer are desirable. In one embodiment, at least one dye is
incorporated into the polymer sensor matrix either by reacting the
dye with the polymer to form a dye-polymer compound, or by
physically combining the dye and polymer to form a composite
mixture of the two materials. In an alternative embodiment,
conjugated dyes, such as acryloyl fluorescein and others, may be
utilized where it is desirable to incorporate the dye directly into
the polymer sensor material by way of covalent bonding.
[0071] While the sensor dye may be either a chromophore-type or a
fluorophore-type, a fluorescent dye is preferred because the
strength of the fluorescent signal typically provides a better
signal-to-noise ratio and improves detection of target analytes. In
the most preferred embodiment, polarity-sensitive dyes or
solvatochromic dyes are utilized. Solvatochromic dyes are dyes
whose absorption or emission spectra are sensitive to and altered
by the polarity of their surrounding environment. Typically, these
dyes exhibit a shift in peak emission wavelength due to a change in
local polarity. Polarity changes which cause such wavelength shifts
can be introduced by the polymerized matrix used for a particular
sensor family, by the presence of a target analyte, or by the
combination of the polymer matrix and analyte interaction with the
dye. The change in polarity creates a characteristic optical
response signature which is useful for detecting specific target
analytes. One preferred solvatochromic dye is Nile Red, available
from Eastman Kodak (Rochester, N.Y.). Nile Red exhibits large
shifts in its emission wavelength peak with changes in the local
environment polarity. In addition, Nile Red is soluble in a wide
range of solvents, is photochemically stable, and has a relatively
strong fluorescence peak. Alternatively, other solvatochromic dyes
such as Prodan, 6-propionyl-2-(N,N-dimethylamino)napthalene, or
Acrylodan, 6-acryloyl (dimethylamino) napthalene, available from
Molecular Probes (Eugene, Ore.), may be employed.
[0072] Additional dyes which are conventionally known in the art
and may be used as dyes in the present invention are those found in
Tables 3-7 and Table 11 of U.S. Pat. 5,512,490 to Walt and Kauer
which is incorporated herein by reference. A particularly useful
reference for selection of candidate dyes such as metallochromic
indicators, including azo and triphenylmethane dyes, and
fluorescent indicators, which may be either mixed with or
conjugated with polymers to form sensors of the present invention,
is Indicators [E. Bishop (ed.), Pergamon Press (New York 1972)]
which is incorporated herein by reference. Another particularly
useful reference for selecting appropriate dye indicators is the
most recent edition of R. P. Haugland, Handbook of Fluorescent
Probes and Research Chemicals (.sub.6th ed.), Molecular Probes
Inc.(Eugene, Ore., 1996) which is herein incorporated by this
reference.
B. Dye-polymer Sensors
[0073] Diverse families and types of optical sensor elements may be
fabricated as sensors and sensor arrays of the present invention by
incorporating sensor dyes, such as metallochromic indicators,
fluorescent indicators, or solvatochromic dyes, within various
polymer matrices. By combining dyes with different polymers, or
combining polymers with different dyes, a wide variety of sensor
materials may be produced which exhibit differential sensitivity to
analytes (see J. White, et al., Anal. Chem., 68:2191-2202(1996)).
By incorporating such dyes in sensor elements made from different
polymer matrices of varying polarity, hydrophobicity, pore size,
flexibility and swelling tendency, unique sensors are produced that
react differently with molecules of individual analytes, giving
rise to distinguishable and characteristic fluorescence responses
when exposed to target analytes. Since the resulting sensor
materials may have different excitation and emission wavelengths,
LEDs, photodiodes, and excitation and emission filter wavelengths
must be appropriated adjusted to match sensor requirements.
[0074] 1. Polymer Selection
[0075] A variety of polymer sensor chemistries may be utilized in
fabricating a wide diversity of dye-polymer sensor materials
according to the method of the present invention. By way of
example, a monomer or oligomer may be selected from any member of
the group of condensation polymers derived from such monomers as
alcohols, dialcohols, amines, diamines, esters, diesters,
carboxylic acids, dicarboxylic acids, diacid chlorides, carbonates,
anhydrides, amides, imides, benzoxazoles, benzthiazoles,
benzimidazoles, quinozalines, aromatic compounds, including
specific polymers such as phenol-formaldehydes, urea-formaldehydes,
melamine-formaldehydes, acetyl compounds, lactones, nylons, or
polyesters. Alternatively, a monomer may be selected from any
member of the group of step-type reaction polymers comprising
sulfones, ethers, phenylene oxides, phenylene oxide ethers,
Diels-Alder-type reactants, urethanes and arylenes. Monomers may
alternatively be selected from any member of the group of vinyl
polymers comprising ethylenes, vinyl chlorides, vinylidene
chlorides, tetrafluoroethylenes, acrylonitriles, acrylamides,
acrylates, methacrylates, acetates, styrenes, methyl styrenes,
vinyl esters, vinyl pyrrolidones, butylenes and butadienes.
[0076] For optical sensors, sensor elements are typically selected
based on distinguishable differences in their characteristic
optical response signatures when illuminated by excitation light
energy in the presence of a target analyte. In fabricating polymer
sensor arrays, polymer sensor elements are selected which have
characteristic optical response signatures when mixed with a dye
compound and illuminated by excitation light energy in the presence
of a target analyte. Thus, preferred optical sensor materials for
sensor arrays are selected based on both physical and chemical
differences in sensor types which, in combination with a reporter
dye compound, produce a characteristic optical response signature
in the presence of the analyte when illuminated by excitation light
energy.
[0077] The following monomer, polymer and copolymer compositions
and their derivatives would be particularly useful as candidate
polymer materials for dye-polymer optical sensors of the present
invention: polyethylene glycol, polycaprolactone, polyarylamide,
methyl methacrylate [MMA], 2-hydroxyethyl methacrylate, siloxane,
dimethylsiloxane, acrlyamide, methylenebisacrylamide [MBA], poly
(1,4-butylene) adipate, poly (2,6-dimethyl-1,4-phenyleneoxide)
[PDPO], triethoxysilyl-modified polybutadiene (50% in toluene)
[PS078.5], diethoxymethylsilyl-modified polybutadiene in toluene
[PS078.8], acryloxypropylmethyl-cyclosiloxane [CPS2067], (80-85%)
dimethyl-(15-20%) (acryloxypropyl) methylsiloxane copolymer
[PS802], poly(acryloxypropyl-methyl)siloxane [PS901.5], (97-98%)
dimethyl-(2-3%) (methacryloxypropyl)methylsiloxane copolymer
[PS851], poly(acrylonitrile-butadiene-styrene)[PABS], poly(methyl
methacrylate), poly(styrene-acrylonitrile 75:25) [PSAN],
acryloxypropylmethylsiloxane-dimethylsiloxane copolymer,
methylstyrenes, styrenes, acrylic polymers, and methylstyrene
divinyl benzene.
[0078] 2. Polymerization Initiators
[0079] In fabricating dye-polymer sensors of the present invention,
polymerization of prepolymer mixtures of desired monomer
combinations may be achieved by thermal polymerization,
condensation polymerization, photoinitiated polymerization, or
either crystallization or precipitation from solution followed by
annealing.
[0080] In one preferred embodiment, thermal polymerization may be
utilized either with or without the addition of an initiator. In
one embodiment, initiators may be employed to control the rate of
thermal polymerization. Since it is often desirable to carry out
polymerization of monomer mixtures at low temperature to prevent
side reactions, the selection of thermal initiators is generally
restricted to organic peroxides, such as dialkyl peroxides or
diacylperoxides, organic hydroperoxides, azo compounds, such as
azobisisobutyronitrile, and organometallic reagents, such as silver
alkyls. Alternatively, thermal initiation may be accomplished by
redox agents, for example, in aqueous solutions, a persulfate salt
used in combination with a bisulfite ion reducing agent may form an
intermediate sulfate radical ion and subsequent hydroxyl radical
initiator. Similar redox reaction initiators may be used by
combination of alkyl hydroperoxides and a reducing agent, such as
ferrous ion. Additionally, some monomers, such as styrenes, undergo
free-radical polymerization when heated or exposed to excitation
light energy. Alternatively, anionic or cationic polymerization
catalysts may also be employed.
[0081] In one embodiment, dye-polymer compound synthesis is
accomplished by way of condensation polymerization. With this
method, no initiator is required and polymerization occurs by way
of direct reaction of desired monomers either in the presence or
absence of a catalyst to stabilize a metastable intermediate.
[0082] In one embodiment, photoinitiated polymerization is
utilized. One advantage of photopolymerization is that it offers
greater reaction control than thermal polymerization and enables
spatial control of local polymerization reactions which can be
restricted to regions illuminated by directed light energy.
Photopolymerization may be conducted either with or without a
specific photosensitizer initiator compound. For example, in the
absence of a specific photosensitizer, many candidate monomer
materials that can undergo chain reaction polymerization are
susceptible to photopolymerization since the absorption of light
produces free radicals or ions. Examples of such compounds are
unsaturated monomers such as vinyl alkyl ketones, vinyl bromides,
styrene, methyl methacrylate and isobutylene.
[0083] In one alternative embodiment, a photosensitizer must be
added to the prepolymer mixture of monomers for photopolymerization
of the polymer. Photosensitizers are compounds that absorb light in
a desired region of the spectrum, typically ultraviolet or visible
light, and subsequently dissociate into free radicals or transfer
absorbed energy directly to a monomer. While some thermal
initiators, such as azo compounds and peroxides are also
photosensitizers, many alternative initiators may be used as
photosensitizers even though they do not dissociate thermally at
useful temperatures. Examples of particularly useful
photosensitizers are carbonyl compounds, such as acetone, biacetyl
benzophenone benzoin, or .alpha.-chloroacetone, condensed ring
aromatics, such as anthracene, peroxides, such as t-butyl peroxide
or hydrogen peroxide, organic sulfides, such as diphenyl disulfide
or dibenzoyl disulfide, azo compounds, such as azoisopropane,
azobisisobutyronitrile or aryldiazonium salts, halogen-containing
compounds, such as chlorine, chloroform, carbon tetrachloride,
bromotrichloromethane, bromoform or bromine, metal carbonyls, such
as manganese pentcarbonyl and carbon tetrachloride or rhenium
pentacarbonyl and carbon tetrachloride, and inorganic ions, such as
FeOH.sup.+2 or FeCl.sub.4.sup.-. In one preferred embodiment,
benzoin ethyl ether initiator is utilized.
C. Substrates
[0084] The present invention provides array sensor element
compositions disposed on substrates which may be either inert or
active during analyte sampling and detection. While inert supports
are typically used in conventional sensing devices, the present
invention provides for active dye support materials that enhance
sensor responses to specific analytes by their unique chemical,
physical, adsorption, or optical characteristics. Different
substrate support materials may be employed within a single array
where specific support materials are matched to specific dyes, dye
compounds and dye polymer mixtures to produce enhanced sensor
responses to specific analytes.
[0085] An important innovation in the present inventions is the
development of fibrous substrate supports which enhance sensor
response signals for a variety of dye materials, such as neat dyes,
dye compounds, and dye-polymer mixtures. As shown in FIGS. 17a-d,
FIG. 18, and FIG. 19a-b, substantial sensor response enhancements
have been achieved with the innovative fibrous supports of the
present invention.
[0086] An additional advantageous feature of the present invention
is in providing for removable or interchangeable arrays, array
substrates, or substrate supports to facilitate changing sensor
arrays to match specific analyte sampling and detection
requirements. In one embodiment, multiple layers of array
substrates may be employed for diversification and enhancement of
sensor detection capabilities for identifying both broad and
specific classes of analytes.
[0087] One skilled in the art would recognized that it is generally
preferred to position sensor substrates at the appropriate viewing
angle and distance from light emitting diode excitation light
sources and photodiode detectors so as to provide for optimum
sensor signal generation and detection. In one preferred
embodiment, a separate substrate holder may be provided for
positioning and securing array substrates. In an alternative
preferred embodiment, the sample chamber housing may be configured
for proper positioning and securing array substrates.
1. Conventional Substrates
[0088] As will be appreciated by those in the art, the number of
possible substrate materials are very large, and include, but are
not limited to, glass and modified or functionalized glass,
plastics (including acrylics, polystyrene and copolymers of styrene
and other materials, polypropylene, polyethylene, polybutylene,
polyurethanes, teflons, etc.), polysaccharides, nylon or
nitrocellulose, resins, silica or silica-based materials including
silicon and modified silicon, carbon, metals, inorganic glasses,
plastics, and a variety of other polymers.
[0089] In preferred embodiments, optically transparent substrates
are employed to permit placement of the substrate between LED light
sources and photodiode detectors as shown in FIGS. 6a-b and FIG. 8.
In alternative embodiments, where the LEDs and photodiodes are
placed on the same side of the substrate, optically opaque or
optically absorbing, reflective, and scattering materials may be
employed.
[0090] Where conventional flat, planar, curved or non-planar solid
sensor substrates are used, these substrates are generally
self-supporting and substrate supports are not required but may be
optionally employed.
2. Signal Enhancing Sensor Substrates
[0091] While conventional flat, planar, or curved non-planar solid
sensor substrates may be employed, increased sensor surface area
can arise from depositing dyes on highly convoluted surfaces that
include fine fibrous hairs of different materials, particulates,
porous substrates, or films and substrates suspended within the
sampling stream. With the innovative substrates of the present
invention, these preferred substrate embodiments provide enhanced
contact and interaction between sample target analytes and sensor
elements, increased optical response signal per unit of sensor
geometrical surface area, and increased optical response signal per
unit of sensor volume.
[0092] In preferred embodiments, highly permeable, high surface
area, textured, fibrous or particulate substrates which have
substantial open porosity for unimpeded transport of vapors and
fluids are desired. In preferred embodiments, single or multi-ply
layers of papers, felts, laid, or woven fibrous materials or
fabrics are employed. In alternative embodiments, loosely packed
individual fibrous or particulate materials may be employed.
[0093] In a most preferred embodiment, fibrous substrate materials
are employed for signal enhancement. Important considerations in
selecting fibrous substrates are substrate permeability to vapors,
high accessible surface area per unit volume, response signal
enhancement for specific analytes, how the substrate interacts with
the sample flow to provide open access of its external and internal
surfaces to analytes for interaction with the sensing material.
While particularly useful fiber substrates are porous, lightweight
paper or tissue products, for example Kimwipe.TM. (Kimberly-Clark
Corp., Roswell, Ga.), lens papers, facial tissues, and products
made from cotton, rayon, glass, and nitrocellulose fibers, other
fibrous materials employing natural or synthetic fibers such as
felt, batting, textiles, woven fabrics, yarns, threads, string,
rope, papers, and laminates or composites of such materials would
be equally suitable as long as they possess the requisite fluid
permeability, surface area, surface area to volume ratio, and open
porosity for free transport of vapor and fluid analytes.
[0094] Particularly useful inorganic fibers and fibrous material
compositions are natural and synthetic fibers made from glass,
ceramic, metal, quartz, silica, silicon, silicate, silicide,
silicon carbide, silicon nitride, alumina, aluminate, aluminide,
carbon, graphite, boron, borate, boride, and boron nitride.
Particularly useful natural or synthetic fibers and fibrous
material compositions are polymer fibers made from aromatic
polyamides, nylons, polyarylonitrile, polyesters, olefins,
acrylics, cellulose, acetates, anidex, aramids, azlon, alatoesters,
lyocell, spandex, melamines, modacrylic, nitrile,
polybenzinidazole. polyproplylene, rayons, lyorell, sarans, vinyon,
triacetate, vinyl, rayon, carbon pitch, epoxies, silicones, sol
gels, polyphenylene-benzobis-ozazole, polyphenylene sulfides,
polytetrafluoroethylene, teflon, and low density or high density
polyethylene. In one preferred embodiment, fiber materials that are
highly absorbent and have good dye retention characteristics, for
example the cellulosic fiber known as Lyorell, may be employed.
[0095] In alternative embodiment, fibers may be coated with either
chemical sizing, polymer, ceramic or metallic materials. Chemical
sizing such as modified polyvinyl acetates, organosilanes, coupling
agents, anti-static agents and lubricants may be employed as
appropriate.
3. Chemically-modified Substrates
[0096] In alternative embodiments, the sensor substrates of the
present invention may be chemically or physically modified to
enhance surface area, absorption, adhesion, hydrophobicity,
hydrophilicity, repulsion, discrimination or specificity. In some
embodiments, the substrate my be chemically altered to provide
chemical functionality for interaction with analytes, such as
providing for enhanced affinity, enhanced repulsion, or steric
impediments to analyte adsorption.
D. Sensor Fabrication
[0097] As discussed above, sensors may be fabricated from neat
dyes, dye polymer compounds, such as intrinsically fluorescing dyes
or conjugated dyes, or dye-polymer With respect to signal enhancing
sensor substrate properties of the present invention, one skilled
in the art would generally recognize and understand the intended
meaning of the term "textured" generally referring to material
surfaces which typically have a distribution of surface
topographical features, such as high points (peaks) and low points
(valleys), ranging from +/-100 nm to +/-1000 um RMS, the term "high
permeability" generally referring to materials and material
structures with a high open porosity that provide essentially free,
unimpeded access and convective or diffusive transport to low
viscosity fluids, the term "high surface area" generally referring
to materials that have a surface area of at least 1 M.sup.2/g and
typically refers to surface areas ranging between 2 to 500
M.sup.2/g, the term "high surface area to volume" generally
referring to materials having a surface area to volume ratio of at
least 1 M.sup.2/cm.sup.3 and typically refers to surface area to
volume rations ranging between 2 to 1000 1 M.sup.2/cm.sup.3, the
terms "porous" or "porosity" generally referring to materials
having a distribution of pore sizes ranging from 100 nm to 1000 um,
and the term "high open porosity" generally referring to materials
whose pore distributions substantially comprise open pores.
mixtures applied to convention substrate surfaces or the innovative
fibrous substrates of the present invention Neat dye and
dye-polymer sensor recipes for the sensors used in Examples 1 and 3
are provided below. Recipes for the sensors used in Examples 2 and
4 are provided elsewhere [see J. White, et al., Anal. Chem.
68(13):2191-2202 (1996) which is incorporated herein by this
reference].
1. Neat Dye Sensors
[0098] A Nile Red/chloroform solution is prepared by dissolving 1
mg of Nile Red per 1 ml of chloroform. Fiber substrate sensors are
typically fabricated by applying approximately. 0.2 mL of dye
solution evenly over a 3 cm.times.3 cm area of substrate material.
The solvent is allowed to evaporate, leaving the fibers of the
substrate coated and infiltrated with dye. A sensor element is
prepared by cutting an approximately 4 mm.times.4 mm piece of dyed
substrate to cover the face of a photodiode. A template
representing the photodiode array configuration and photodiode
placement is used to position the sensor element on a glass cover
slip. The sensor is then held in place by taping the edges. Other
methods of securing the sensor are also possible, such as employing
glue or mechanical clamping.
2. Dye-Polymer Mixtures
[0099] Typically, a sensor made from a dye-polymer mixture is
produced by mixing Nile Red solvent solution with a monomer solvent
solution. Generally, in preparing sensors from dye-monomer solution
mixtures, it is preferable to minimize monomer content and maximize
dye content to provide maximum sensor response signal. However,
with some analytes, additional monomer is added to provide optimum
sensor response signal. The upper limit of monomer additions is
generally established by viscosity considerations where low
viscosity solutions are desired for application of thin sensor
layers or coatings to substrates. While most monomer solutions are
prepared with chloroform solvent, some monomers require other
solvents such as methanol and toluene.
[0100] Nile Red/polyethylene oxide (PEO) sensors are prepared from
a solution of 0.007 g of polyethylene oxide dissolved in 1 mL of
chloroform. A Nile Red/chloroform solution is prepared by
dissolving 1 mg of Nile Red per 1 ml of chloroform. 0.01 ml of the
Nile Red solution is added to 1 ml of the monomer solution.
[0101] Nile Red/Poly(N-vinylpyrrolidone sensors are prepared from a
solution of 0.062 g of monomer [PolySciences, Inc., Warrington,
Pa.] dissolved in 1 mL of chloroform. A Nile Red/chloroform
solution is prepared by dissolving 1 mg of Nile Red per 1 ml of
chloroform. 0.01 ml of the Nile Red solution is added to 1 ml of
the monomer cellulose solution.
[0102] Nile Red/Poly (ethyl cellulose) sensors are prepared from a
solution of 0.025 g of ethyl cellulose [PolySciences, Inc.] is
dissolved in 1 mL of a 4:1 mixture of toluene and ethanol. A Nile
Red/toluene solution is prepared by dissolving 1 mg of Nile Red per
1 ml of toluene. 0.01 ml of the Nile Red solution is added to 1 ml
of the monomer solution.
[0103] Nile Red/Poly (dimethylsiloxane) sensors are prepared from a
solution of 1 mL of Poly(dimethylsiloszane) 200 (R) fluid (1000 cP
viscosity) [Aldrich Chemical Co., Milwaukee, Wis.] dissolved in 0.5
ml of toluene. A Nile Red/toluene solution is prepared by
dissolving 1 mg of Nile Red per 1 ml of toluene. 0.01 ml of the
Nile Red solution is added to 1 ml of the monomer solution.
[0104] PBA sensors are prepared from a solution of 0.4 g of
poly(1,4-butylene adipate) in 1 ml of chloroform to which 0.2 ml of
Nile Red chloroform solution (1 mg/ml) is added.
[0105] Pentiptycene-derived phenylenecthynylene polymer 1 [SeeYang
and Swager in J.Am.Chem.Soc. 120:11864-11873(1998)] sensors are
intrinsically fluorescent and do not require dye additions. These
sensors are prepared from a solution of 1.2 mg of polymer in 1 mL
of chloroform.
[0106] For each of the above sensor compositions, sensors are
prepared on conventional substrates by applying approximately. 0.2
mL of the monomer or polymer solution mixture evenly over a 3
cm.times.3 cm area of a glass substrate The solvent is allowed to
evaporate, leaving the substrate coated with dye. The polymer is
cured at room temperature.
[0107] Fiber substrate sensors are typically fabricated by applying
approximately. 0.2 mL of dye, dye-polymer, or fluorescent polymer
solution evenly over a 3 cm.times.3 cm area of substrate material.
The solvent is allowed to evaporate, leaving the fibers of the
substrate coated and infiltrated with dye. The polymer is cured at
room temperature. A sensor element is prepared by cutting an
approximately 4 mm.times.4 mm piece of dyed substrate to cover the
face of a photodiode. A template representing the photodiode array
configuration and photodiode placement is used to position the
sensor element on a glass cover slip. The sensor is then held in
place by taping the edges. Other methods of securing the sensor are
also possible, such as employing glue or mechanical clamping.
[0108] Dow/Alumina sensors are prepared from a solution of 0.062 g
of dimethyl siloxane dispersion coating (Dow Corning, Midland,
Mich.) dissolved in 2 ml of toluene. A Nile Red/toluene solution is
prepared by dissolving 1 mg of Nile Red per 1 ml of toluene. 0.05
ml of the Nile Red solution is added to 1 ml of the monomer
solution.
[0109] PDPO/Alumina sensors are prepared from a solution of 0.2 g
of poly(2,6-dimethyl-1,4-phenyleneoxide) (Aldrich Chemical,
Milwaukee, Wis.) dissolved in 1.5 ml of chloroform. A Nile
Red/toluene solution is prepared by dissolving 1 mg of Nile Red per
1 ml of toluene. 0.375 ml of the Nile Red solution is added to 1 ml
of the monomer solution.
[0110] PC/Alumina sensors are prepared from a solution of 0.19 g of
polycaprolactone (2,6-dimethyl-1,4-phenyleneoxide) (Aldrich
Chemical) dissolved in 1.5 ml of chloroform. A Nile Red/toluene
solution is prepared by dissolving 1 mg of Nile Red per 1 ml of
toluene. 0.05 ml of the Nile Red solution is added to 1 ml of the
monomer solution.
[0111] For each of the above polymer/alumina sensor compositions,
sensors are prepared on conventional substrates with alumina power
additions. 150 mesh alumina powder (Aldrich Chemical) is treated
with a 1 mg/ml solution of Nile Red in toluene. The alumina is
washed in toluene to remove excess dye and allowed to dry
overnight. A droplet of the dye-monomer-solvent solution is applied
to a glass coverslip substrate and the Nile Red stained alumina
powder is sprinkled over the monomer solution droplet. The
monomer-alumina mixture is then polymerized at room
temperature.
[0112] The Celluse/Alumina/Cellulose fiber optic sensors described
in Example 4 are prepared from the ethyl cellulose solution
described above. Fiber ends were dipped in the ethyl cellulose
preparation, allowed to air dry for 1 min, and dipped in the Nile
Red treated alumina powder. After air drying for 1 min, the fiber
was dipped in the ethyl cellolose solution again and air cured.
[0113] The PC/PSAN/Alumina fiber optic sensors described in Example
4 are prepared from a 0.2 ml solution of 0.2 g of polycaprolactone
dissolved in 2.0 ml of chloroform and a 0.2 ml solution of 0.2 g of
poly styrene-acrylonitrile dissolved in 2.0 ml of chloroform. A
fiber end is dipped in the polymer mixture, allowed to air dry for
approximately 1 min, and then dipped into the Nile Red treated
alumina powder (see above) and cured at room temperature.
[0114] The Cellulose/PDPO/Beads fiber optic sensors described in
Example 4 are prepared from a 0.2 ml solution of 0.2 g of poly
(2,6-dimethyl-1,4-phenyleneoxide) (Aldrich Chemical) dissolved in
1.5 ml of chloroform and a 0.2 ml solution of the ethyl cellulose
solution described above. The beads were 80-100 mesh alumina
stained with a 1 mg/1 ml solution of Nile Red in toluene and washed
in toluene. A fiber end is dipped in the polymer mixture, allowed
to air dry for approximately 1 min, and then dipped in the treated
alumina beads and cured at room temperature.
[0115] The RMS-044 fiber optic sensors described in Example 4 are
prepared from a solution of 0.746 g of 4-6% (methacryloxyproply)
methyl-siloxane, dimethyl siloxane copolymer (United Chemical
Tech.) in 1.8 ml of chloroform to which 60 mg of BEE photoinitiator
is added. A fiber end is dipped in the polymer solution and the
polymer is photo-polymerized by exposing the fiber end to 4500
mW/cm.sup.2 of ultraviolet light for 17 seconds. The
photo-polymerization method was described previously [see J.White,
et al., Anal. Chem. 68(13):2191-2202 (1996)].
[0116] The PS901.5 fiber optic sensors described in Example 4 are
prepared from a solution of 0.5 ml poly(acryloxxypropylmethl)
siloxane in 0.5 ml of chloroform to which 20 mg of BEE
photoinitiator is added. A fiber end is dipped in the polymer
solution and the polymer is photo-polymerized in the same manner as
the RMS-044 sensor above.
[0117] The PS802/PS901.5 fiber optic sensors described in Example 4
are prepared from a solution of 0.6 ml of (80-85% dimethyl (15-20%)
acryloxypropyl) methylsiloxane copolymer in 0.4 ml of chloroform to
which 60 mg of BEE initiator is added. 0.1 ml of this solution is
mixed with 0.1 ml of the PS901.5 solution (see above) and a fiber
end is dipped in the copolymer solution. The copolymer mixture is
photo-polymerizeds in the same manner as the RMS-044 sensor above
except the exposure time was 20 seconds.
II. Sensing System
[0118] The innovative sensor and sensing system of the present
invention provides for a rapidly responding, relatively
inexpensive, dynamically configurable, intelligent, portable
artificial sampling device. Innovative features of the device and
method of the present invention include innovative sensor
substrates for enhancing response signals, improved analyte
sensitivity and discrimination, real-time ambient environment
sampling, smart training and sampling modes, and intelligent,
real-time modulation and control of the sampling and detecting
methods and hardware components for adaptive learning and
optimization of sampling conditions for specific sampling
environments and target analytes.
[0119] The innovative device delivers analytes (odors) in a
controlled, pulsatile manner (sniff) to fluorescence-based sensor
array and detector array system that generates analog electrical
signals. The number of sensors, detectors, and sampling time points
are arbitrary and can be made larger or smaller depending on the
classes of analytes that are being targeted for detection. These
analog signals are amplified and filtered by a
pre-amplifier/amplifier module and digitized to 12 bits by an
analog/digital conversion module for storage in a computer memory
module. All attributes of the sensing process, including odor
delivery, sampling, analysis, detection and identification are
under programmable software control via a computer.
[0120] The sensing device must be trained in order to recognize
specific analytes. Training consists of delivering a known set of
various analytes to the device, one analyte at a time, and storing
matrices of values that are a spatio-temporal signatures of each
analyte in memory. When an unknown fluid is to be sampled after
training, it is delivered to the device and a matrix of values
acquired from the unknown is compared to matrix templates for the
variety of analytes stored in memory during the training phase. The
best match between the unknown and the library of stored matrices
is then determined using a number of different algorithms. In one
embodiment, the algorithm looks for the best match after
calculating the sum of the squared differences between each point
in the stored and unknown matrices.
[0121] The sensing system provides output results in a variety
formats including, but not limited to screen displays, plots,
printouts, database files, and synthesized voice messages. A
typical sensor output is shown in FIG. 20 where a plot of the
unique spatio-temporal fluorescence responses of the array sensors
to various analytes is provided.
A. Device Overview
[0122] The sensing device of the present invention comprises a
sampling chamber housing an analyte delivery system and a
multi-channel array comprising light emitting diodes (LEDs)
focussed through an array of excitation filters onto individual
sensor elements of a sensor array. An array of photodiodes,
filtered with an array of emission filters, detects emitted light
energy produced by illuminating the sensor elements with LED
excitation light during interaction with analytes that are drawn
into the sample chamber by the analyte delivery system. The ambient
temperature, humidity, and particulate levels in the sample chamber
may be controlled for improved reproducibility in sampling under a
variety of environmental conditions. The changes in emitted light
detected by the photodiode array for each sensor element are
digitized by either 12 bit or, alternatively, 24 bit
analogue-to-digital converters and stored in a computer memory
module. Analyte sampling, detection, and identification are
controlled by a programmable microcontroller directed by smart
sampling and detection algorithms. The device provides for fast,
high gain, low noise, real-time sampling, detection and
identification of a variety of vapor analytes with high sensitivity
and low detection limits, typically in the sub ppm to ppb
concentration range. The innovative device further provides for
intelligent sampling and detection through real-time, dynamic
modulation of sampling conditions and detection criteria with
real-time feedback control for optimizing device sensitivity,
discrimination, and detection of a variety of analytes.
B. System Components
[0123] The sensing device of the present invention provides for
generating optimized signals for different dye/polymer combinations
by using different excitation and emission wavelengths for
different sensor types. Unlike conventional sensing devices, with
the present invention, this can be achieved simultaneously while
sampling the entire array of sensing elements in parallel using an
array of individual LED-sensor-photodiode sensing channels
operating at appropriate wavelengths for a variety of
sensor-analyte combinations.
[0124] The sensing device generally provides the basic function
comprising analyte delivery and control (i.e. manipulation of
spatial and temporal distributions; control over temperature,
humidity, and duty cycle), detection by a sensor array and
transduction of sensor signals into a manipulatable format,
analysis of transduction output events, and dynamic feedback
control over analyte delivery, detection and analysis for
intelligent sampling and detection and optimization of sensor
sensitivity and analyte discrimination.
[0125] FIGS. 3 and 4 provide schematic block diagrams showing the
general modular design and configuration of the sensor array and
sensing system components. Details of the sample or analyte
delivery module are shown schematically in FIGS. 6a-b. A detailed
schematic of the sensor array configuration of LEDs, excitation
filters, sensor elements, emission filters, and photodiodes is
provided in FIG. 8. The relative locations and configuration of
LEDs, sensor elements, photodiodes, and emission/excitation filters
are shown in FIG. 13. Detailed circuit schematics are provided for
LED array controls (FIG. 5), analyte delivery fans and control
valve controls (FIG. 7), photodiode preamplifier module (FIG. 9),
amplifier module (FIG. 10), connections into analog to digital
conversion module (FIG. 11), and computer control module and
pre-amp/amp power board (FIG. 12).
[0126] These modular components are described in detail in the
following sections.
C. Analyte Delivery
1. Overview
[0127] For reliable and reproducible sampling of ambient fluids, it
is important to standardize sampling and sensing conditions by
controlling the delivery and presentation of analytes to the sensor
array. In a preferred embodiment, the analyte deliver system
provides feedback control over sample temperature, humidity,
flow-rate, and the rise and fall times, duration, and frequency of
analyte delivery.
[0128] One embodiment of the analyte delivery system is shown in
FIGS. 6a-b and FIG. 8. Generally the sensing chamber consists of a
rectangular tube through which the analyte vapor passes. The
sensing array with opposed light emitting diode light sources and
photodiode photodetectors with sensor elements is placed within a
sample chamber. In this configuration the incoming fluid stream
generated by a gated negative pressure (i.e. a sniff pump such as a
fan, pump, `mesopump`, bellows, or their equivalents) causes the
fluid stream to be drawn into the sensing chamber and to be
expelled to the ambient environment by the negative pressure
source. In this manner, analyte vapor pulses are delivered to the
sensing array from ambient pressure sources. The sensing chamber
can be of the form of a simple tube, as described above, or may
assume any shape that may improve or optimize the delivery of the
analyte pulse to the sensor array, including complex shapes modeled
after the structure of the nasal cavity of animals. In one
embodiment, complex cavities with multiple baffles are used to
prevent ambient light and ambient air movements from interfering
with the generation of standardized pulses of analyte to the sensor
array.
[0129] Generally, the sensing chamber includes: a) a means for
controlling temperature, humidity, flowrate, rise and fall times
and frequency of the applied vapor pulses; b) a means for
controlling the surface properties of the sensing and non-sensing
areas of the chamber (liquid, mucus, or gel lining) in order to
impart chromatographic surfaces to the sensing area and/or
humidify, dehumidify, or distribute the analyte to the sensory
surface, or to optimize response of the sensing chemistry; c) a
means for aerodynamic control over chamber shape which may either
be held constant for the duration of analyte delivery or modulated
by feedback control during analyte delivery; and d) a means for
active, dynamic feedback control over shape, duration, flowrate,
temporal envelope, and frequency of analyte sampling (sniffing).
Such feedback may be derived from examining the spatio-temporal
response patterns from the sensor array produced by prior analyte
sampling.
2. Sensor Chamber Design
[0130] A cross-sectional view of a sampling chamber embodiment
showing 9 detection sites is provided in FIG. 8. In designing the
sampling chamber, it was necessary to configure the chamber,
sensors, LEDs and photodiodes to comply with focal length
dimensions of the integral lenses that were incorporated into the
LEDs and photodiodes. Focal lengths of the integral lenses were
measured and, based on these dimensions, the width of the sample
chamber and the positions of the sensors within the sample chamber
were arranged such that the sensors were optimally illuminated by
the LEDs and optimally observed by the photodiodes at their
respective appropriate focal distances.
[0131] The present invention provides for control over the sensing
chamber environment where, for example, ambient light levels,
aerodynamic flow conditions, sample humidity and temperature can be
measured, standardized, controlled, adjusted, or modulated for
different analyte detection tasks.
[0132] The sensing chamber can be optimized for its aerodynamic
properties by placing the detectors in cavities of various shapes.
In one embodiment, the sensors may be placed at a bend in the flow
path. In an alternative embodiment, the sensors may be located on
the side of the straight flow path. Since the present device is
unique in its use of ambient flow sniffing and dynamic information
gathering, the present invention provides an opportunity to exploit
the aerodynamic properties of complex spaces for improved sampling
performance. For example, the chamber space may be configured to
mimic the actual shape of the mammalian nasal cavity, or,
alternatively, it may be configured to provide preferred fluid flow
or aerodynamic design features. These embodiments would complement
the design capability of the present invention which provides for
static and dynamic control and modulation of inhalation and
exhalation during sampling.
[0133] In one embodiment, humidification of the chamber and analyte
sample is achieved by humidifying the incoming (inhalation) air
stream in the entry nozzle and outgoing (exhalation) air stream in
the exhaust pathway, both of which pass over the sensor array. In
one method, humidification is accomplished by placing an absorbent
material, such as filter paper, within the air tubing. The
absorbent surfaces are connected by wicks to vials of water,
thereby keeping them moist. In alternative embodiments, the
humidity of the source may also be modulated by spraying water mist
on the sampling area before sniffing. This will frequently increase
the volatility of odors and improve detectability. While other
humidification methods may be employed, the primary objective is to
provide a means for balancing the humidity levels of the ambient
air with those of the analyte source. In a preferred embodiment,
precise control of humidity in the chamber could be accomplished by
using specific chamber sensors to detect humidity levels which
supply feedback to a moisture metering system.
3. Sniffing Fans and Valve System
[0134] Ambient odors are drawn into the sampling chamber (made in
house) in a pulsed fashion by two continuously running fans (for
example, Panaflo DC, brushless, 12 V, 270 mA, 19.7 cfm)--one for
generating inhalation (see FIG. 6a), one for exhalation (see FIG.
6b) through the sampling chamber. The inhalation or exhalation
flows are gated by butterfly valves (made in house), controlled by
servo motors (Hobbico, high power, mini servo CS-35 from Tower
Hobbies, PO Box 9078, Champaign, Ill. 61824-9078) governed by the
computer under software control. During inhalation, flow from the
inhalation fan is connected to the sensing chamber (via standard 1"
ID PVC plumbing materials) and flow from the exhalation fan is
connected to exhaust (see FIG. 6a). During exhalation, flow from
the exhalation fan is connected to the sensing chamber and the
inhalation fan is connected to exhaust (see FIG. 6b). This control
valve arrangement prevents the build up of pressure pulses and
keeps flow rates reasonably constant for both in- and ex-halation
and for rapid switching between the two. Computer control of the
servo motors determines the duration, rise and fall times, and
frequency of sniffing. It is important to note that these
parameters (along with the others described below) can be changed
in real time during data acquisition in order to optimize the
signals of interest. FIG. 7 shows the interface board between the
servo motors and computer.
D. Sensor Array
1. Sensor Elements
[0135] As discussed elsewhere, sensing elements are composed of
either dye, dye compounds, or dye-polymer mixtures applied to
removable sensor substrates. In one embodiment, thin films of
either dye, dye compounds, or dye-polymer mixtures are deposited on
a flat plastic or glass substrate. In preferred embodiments, dye,
dye compounds, or dye-polymer mixtures are deposited directly onto
fibrous supports made from natural or synthetic cellulose,
polymers, glasses, ceramics, metallic, or other materials. The use
of fibrous dye substrates dramatically increases the magnitude of
the response signals, which improves analyte detection and
discrimination of the device. In an alternative embodiment, thin
dye-polymer films or dye-containing fiber supports can be suspended
freely across a perforated removable solid substrate which is
placed in the center of the air flow stream, thereby exposing both
sides of the sensor to vapor phase analyte.
[0136] An innovative feature of the sensing device is the use of
interchangeable, removable sensor substrates. Supporting the sensor
array on easily removable substrates, facilitates rapid changing of
sensing sites during sampling for improving the sensitivity and
discrimination for specific analytes in a variety of sampling
applications. This feature further provides for rapid screening of
dyes, dye compounds, and dye-polymer mixtures for evaluating new
sensor materials and analytical detection algorithms.
[0137] The size, thickness and surface area of sensor element sites
may be modified to optimize sensitivity and discrimination and to
efficiently couple sensor elements to light sources and detectors.
Generally, a larger sensor geometric area and a close matching of
the sensor element geometric area with photodetector area will
provide better sensitivity.
2. Array Configuration
[0138] The cross-reactive sensor array of the present invention may
comprise either analyte-specific or broadly responsive sensor
elements. The number of sensor array elements can be configured for
specific sampling applications requirements. Specific sensors for
defined analytical tasks can be chosen from among the many possible
sensing element sites present in the array. Sensor and array
configurations may be modified through the addition of additional
LED-sensor-photodiode-filt- er channels depending on the
requirements of a particular analyte discrimination task.
[0139] In one preferred embodiment, multiple sensor arrays and
array substrates may be deployed in the sampling chamber. Such
multiple arrays may comprise a series of hierarchically organized
sensor arrays such that the first interaction and sampling of the
analyte is with a broadly responsive sensor array and,
subsequently, the analyte sample is automatically diverted for
additional sniffs, on the basis of analytical information fed back
from the computer, to specific second order arrays designed to
detect and identify the specific type of analyte. Thus, a plurality
of sensing arrays may be arranged hierarchically so that ever finer
discriminations can take place successively along the pathway.
Additionally, the longevity of sensors can be extended by redundant
arrays that are protected from exposure until needed; by delivery
of analytes as short pulses, and by reducing light exposure by
rapidly pulsing LEDs. Low light excitation levels can be used if
high sensitivity photodetectors such as avalanche photodiodes are
employed. Rapid short pulsing of analytes prevents sensing surfaces
from ever reaching equilibrium.
[0140] For enhanced, smart mode operation, the number of array
sensors used in sampling or detecting an analyte may be modified,
in real-time during either actual sampling or post-sampling data
analysis using "on-the-fly" intelligent feedback control. By way of
example, if a specific sensor is unresponse to a particular analyte
sample, the corresponding sensing channel may be automatically
removed from consideration by a smart sampling or analysis
algorithm provides feedback control to the microcontroller. In
addition, the weighting of individual sensors in the analysis and
detection algorithm may be adjusted based on the signal
contribution of individual sensors. Given that individual sensors
have different breadths and peaks of response, sensor weighting
will vary for different analytes.
[0141] In one preferred embodiment a 32 channel sensor array is
employed. It is anticipated that an array of thirty-two sensor
elements should have the capability of detecting at least 1000
different analyte types, as long as the sensors materials employed
provide sufficient diversity in their analyte detection capability
and are appropriately broad in their spectra of response. While the
results presented in Examples 1 through 4 were generated for array
sizes ranging from nine sensor elements to thirty-two elements, one
skilled in the art may increase or decrease both the size of the
sensor array and number of sensing channels, following the
teachings disclosed herein, for meeting specific sensing
application requirements.
E. Optical Detection System
[0142] Typically, epi-illuminating optics are employed with
conventional optical sensing systems. Epi-illuminating optics
require relatively complex dichroic mirror arrangements for each
channel where a different excitation and emission wavelength is
used. Thus, in the epi-illumination format an excitation filter, a
dichroic mirror, and an emission filter are required for each
wavelength. The sensing system of the present invention employs a
trans-illumination configuration where only excitation and emission
filters are needed. Since the epi-illumination mode typically
requires critical optical component alignment and is sensitive to
vibration and movement, the trans-illumination mode of the present
invention is advantageous for robust, compact, portable sensing
devices for field sampling of ambient environments.
[0143] A schematic diagram of the optical detection system of the
present invention is provided in the block diagram of FIG. 3. FIG.
8 provides a cross-sectional view of the sampling chamber that
schematically shows the configuration and relative orientation of
individual LED-photodiodes-optical filters-sensor pairings within
the sampling chamber housing. For simplicity, the cross-sectional
view in FIG. 8 shows only three sensing channels, comprising three
LED-photodiode-filter-senso- r channel pairings. A schematic
exploded view of a nine sensor array configuration is shown in the
inset of FIG. 8. It is important to note that the partial array
configurations shown in FIG. 8 are merely used to demonstrate, by
way of example, the relative orientation and positioning of the
sensors, filters, photodiodes and LEDs in the sampling chamber and
are not intended to indicate any; limitation in the size of sensor
arrays that may be employed in the present invention. The actual
sensing device of the present invention may employ larger or
smaller arrays and any number of sensing channels with
corresponding LED-photodiode-filter-senso- r parings. For example,
in one preferred embodiment, 32 LED-photodiode-optical
filters-sensor channel parings are employed. The number of sensor
array channels may be increased or decreased depending on specific
sampling applications and analyte discrimination requirements.
1. Array Components Configuration
[0144] The configuration and relative orientation of LEDs,
photodiodes, excitation filters and emission filters, sensors and
sensor array substrate is shown schematically in FIGS. 13a-b. While
an eight sensor-LED-photodiode-filter module is shown in FIGS. 13a
by way of example, larger and smaller modules and arrays may be
constructed based on specific sampling and detection needs. For
example, in one preferred embodiment, a 32 element sensor array may
be assembled from four modules aligned side-by-side with eight
sensors in each module. As shown in FIG. 13a, a plurality of LEDs
are mounted on a nominally 30 mm.times.30 mm.times.6 mm black
plexiglass support by drilling two columns of four 3 mm holes in a
2.times.4 array configuration. The LEDs are press fit into the
mounting holes and may be readily removed for replacement. A
photodiode support with the same dimensions is used for mounting a
plurality of eight photodiodes in a 2.times.4 array configuration.
Both the LED and photodiode arrays are mounted in columns with pair
row spacings of 6 mm center to center and interpair spacings of 8
mm center to center. Column spacing for both the LED array and
photodiode array is 15 mm center to center.
[0145] As shown in FIG. 13a, 12.5 mm (1/2") diameter excitation
filters are mounted on an approximately 30 mm.times.30 mm.times.6
mm excitation filter support formed by drilling. four 1/2" holes in
a black plexiglass support plate to accommodate the filters in a
2.times.2 array configuration. Other filter assembly
configurations, containing a larger or smaller filter array with
larger or smaller filters may be employed in other embodiments. A
similar emission filter support with the same dimensions as the
excitation filter support is fabricated for mounting four emission
filters. The emission filters and excitation filters are mounted to
their respective supports with conventional set screws. The
resulting excitation filter support assembly is attached directly
to the front face of the LED support assembly and the emission
filter support assembly is attached directly to the front face of
the photodiode support assembly with conventional mounting
screws.
[0146] A plurality of sensor elements are applied either directly
to a transparent sensor array substrate, for example a glass
coverslip, as coatings or droplets. Alternatively, where porous or
fibrous sensing elements are employed, these may be taped, glued,
or clamped to a transparent sensor array substrate, or suspended
over openings or perforations in an array support substrate which
may be either transparent or opaque. As shown schematically in FIG.
13b, removable, interchangeable sensor array substrates, or array
support substrates, are mounted flush with the front face of the
emission filter support using an substrate support holder. The
substrate support holder is formed by gluing a U-shaped substrate
support frame and a U-shaped substrate support facing to the front
fact of the emission filter support. The sensor array substrates,
or array support substrates, are slidably mounted in a slot or
channel formed by the substrate support frame, support facing and
front face of the filter support as shown in FIG. 13b. The
substrate support assembly provides for rapid removal and
replacement of the interchangeable array substrates or array
support substrates.
[0147] The sensor array may comprise either a single sensor array
module, as shown in FIG. 13a, or a plurality of sensor modules
aligned edge-to-edge to form a multi-module array containing a
large number of sensor elements. The bottom edge of both the
LED-excitation filter module support assembly and the
photodiode-emission filter-sensor module support assembly are
secured to a chamber support plate with conventional mounting
screws. In this configuration, the excitation filter side of the
LED assembly faces the sensor array side of the photodiode
assembly. The LED and photodiode modules, or plurality of modules,
are preferably aligned parallel to one another with spacing between
the two modules adjusted to optimize illumination of the sensor
array elements by the LED array. In one preferred embodiment shown
in FIG. 13a, this spacing is approximately 9.5 mm. In one preferred
embodiment, a 32 sensor array is formed by mounting four eight
sensor modules ton the chamber support plate. Other configurations
using larger or smaller sensor modules and a fewer or greater
number of modules may be employed to accommodate smaller or larger
arrays by adjusting the size of the LED, photodiode, filter and
sensor supports and chamber support plate and adjusting the spacing
between opposing LED and photodiode modules to optimize
illumination of sensor array elements by the LED array.
2. Excitation/Emission Filters
[0148] Commercially available, optical bandpass excitation filters
for LED light sources and emission filters for photodiode detectors
were obtained from Andover Corp. (Salem, N.H.). While these filters
are available in 1/4 to 11/2 inch sizes, 1/2 inch filters were used
in preferred embodiment. By way of example, FIG. 13 shows
schematically the relative orientation, configuration and spacing
of excitation and emission filters for an embodiment which employs
32 sensors and sensing channels. For simplicity, FIG. 13 shows only
one of four eight-sensor modules employed in a 32 channel sensor
array. In this embodiment, with four sensor modules, 16 Excitation
filters are arranged in a 2.times.8 array with a center to center
distance of 15 mm. With this embodiment, each emission filter
covers a pair of two adjacent photodiodes having a 6 mm center to
center spacing. In this particular embodiment, the.32 sensor
elements in the array were aligned with the center of the
LED-photodiode pair sight line. Other embodiments are envisioned
where each sensor channel has its own individual excitation and
emission filter or where more than two sensor channels share each
excitation and emission filter.
[0149] The excitation and emission filters that were utilized for
specific sensor materials in one preferred embodiment are listed
below. Note that the filters are designated by center wavelength,
followed by "FS", then the bandpass at 50% amplitude.
[0150] 1. Nile Red:
[0151] excitation--533FS40
[0152] emission--600FS10, 610FS10, 620FS10, 633FS10, 640FS10,
650FS10, 660FS10
[0153] 2. Nile Red+Poly(N-vinylpyrrolidone):
[0154] excitation--533FS40
[0155] emission--600FS10
[0156] 3. Nile Red+Poly(ethyl cellulose):
[0157] excitation--533FS40
[0158] emission--61OFS10
[0159] 4. Nile Red+Poly(dimethyl siloxane):
[0160] excitation--533FS10
[0161] emission--633FS10
[0162] 5. Nile Red on Millipore glass filter:
[0163] excitation--533FS40
[0164] emission--650FS10
[0165] 6. Pentiptycene-derived phenylenecthynylene polymer 1:
[0166] excitation--460FS10 // 430FS10
[0167] emission--488FS10, 500FS10 // 470FS10, 510FS10
[0168] 7. 4-(dicyanovinyl)julolidine (DCVJ):
[0169] excitation--460FS10 // 430FS10
[0170] emission--488FS10, 50OFS10 //470FS10, 510FS10
3. Excitation Light Sources/LEDs
[0171] Illumination of sensor elements with excitation light energy
may be accomplished with any appropriate light source. Thus,
filtered light emitting diodes (LEDs), solid state lasers, or
incandescent light sources of the appropriate wavelengths for the
dye indicators being used may be employed. In a preferred
embodiment, each LED light is passed through an excitation filter
matched to a specific sensor element dye excitation wavelength.
Where excitation filters are employed, broad band ("white") LEDs
with appropriate wavelength filters may be used.
[0172] Unlike conventional sensors, by providing individually
filtered sensing channels, the present invention enables
simultaneous sampling at multiple excitation wavelengths and
multiple emission wavelengths with different sensor elements. The
present invention uniquely provides for individual control over the
amplitude, duration, and duty cycle of illumination for each
sensing channel in the array. Control over noise is exerted by
feedback. Control over response to ambient light and optimization
of signal detection, including reduction of dye bleaching, is
accomplished by switching and modulating LED output and coordinate
amplifier detection at various frequencies, ranging from kilohertz
to megahertz. Control over ambient light interference may be
achieved by phase locked LED flashing and photodiode detection.
[0173] In the present invention, sensor elements are illuminated
directly by focussed, light emitting diodes (LEDs) of the correct
wavelength for each sensor dye material. Other advantages achieved
from using LED excitation light sources are low power requirements,
cooler operating temperatures, and high light output over small
area. Additionally, by employing LED light sources for each array
sensing channel, each LED channel can be rapidly and independently
switched electrically without use of a mechanical shutter. The LED
channels can be individually modulated electrically at high rates
by feedback from the microcontroller. In addition, the LED channels
can be individually filtered for presenting different excitation
wavelengths in parallel, thereby avoiding serially and mechanically
switching filters during array measurements.
[0174] For delivering green light with a peak at 530 nm, E903
Megabrite LEDs (Gilway Technical Lamp, Woburn, Mass.) run at
maximum current are used. With this LED model, excitation of the
dye Nile Red has been achieved both without excitation filters,
using the raw LED output and with excitation filters with peaks at
532 nm+-10 nm. For blue light with a peak at 430 nm, cat. #25-346
blue LEDs manufactured by Everlight (Hosfelt Electronics, Inc.,
Steubenville, Ohio) run at maximum current are used. Excitation of
fluorescent detector materials in the blue have used filters from
Andover with a peak at 430 nm+-10 nm.
[0175] The LED's are turned on and off under computer control.
Since these devices can respond at high speeds, up to megahertz
frequencies, they are typically flashed at kilohertz frequencies in
order to reduce bleaching. Such switching speeds cannot be achieved
using mechanical shutters. The rapid switching capacities of LED's
are utilized to flash them on and off in order to reduce sensor
bleaching during data acquisition. This is achieved by
pre-bleaching sensors before sample sniffs and by reducing total
light exposure by shortened duty cycle during sample sniffs. This
is accomplished by rapidly flickering the LED so that light is only
on during the time when data are being taken and then turned off
between data points and between trials.
[0176] The electrical circuit controlling the LED's, which are
connected in parallel, is shown in FIG. 5. In this circuit a Radio
Shack power IFR510 MOSFET (Tandy Corp., Fort Worth, Tex.) is
controlled by one of the input/output lines (see pin 35 of
connector J2 from the computer in FIG. 12) under software
control.
4. Detectors/Photodiodes
[0177] While a variety of photodetectors such as photomultiplier
tubes (PMTs), charge-coupled display device (CCD) detectors,
photovoltaic devices, phototransistors, and photodiodes may be used
for detecting sensor response signals, in a preferred embodiment,
filtered photodiode detectors are employed. In another preferred
embodiment, highly sensitive avalanche photodiodes may be employed.
Photodiode detectors have distinct advantages compared to
conventional CCD camera detectors since they enable independent
control and modulation of individual channel optical filtering,
current/voltage conversion, signal amplification,. and temporal
filtering. Other specific advantages are low power consumption,
relatively simple electronic circuitry, high sensitivity,
configurability, multiple array formats (e.g. circular, square, or
linear arrays), fast high frequency response at megaHertz
frequencies, low noise, wide dynamic range, and use with low
frequency circuits.
[0178] In the sensing device of the present invention, an array of
filtered photodiodes is employed where each filtered photodiode is
either aligned with one filtered LED or, alternatively, groups of
filtered photodiodes may be illuminated by a single filtered LED.
The individual photodiodes are each aligned with an individual
sensor element site with an optical emission filter that is
appropriate for the specific dye employed by the individual sensor.
Different emission filters may be used for each photodiode or,
alternatively, one emission filter may be shared by multiple
photodiodes. Photodiode signal noise is controlled by feedback.
Additionally, feedback control is exerted. over the signal sampling
duration and time course. Differential signal inputs may be
employed with a separate control sensor and individual sampling
sensors. In one preferred embodiment, highly sensitive avalanche
photodiodes may be used to permit lower required LED intensity for
sensor of excitation and for reducing detector noise.
[0179] In one embodiment commercially available EG&G VTP 1232
photodiodes (EG&G, Inc, Gaithersburg, Md.) and commercial 12.5
mm emission filters (Andover Corp., Salem, N.H.) were used.
Specific emission filters used in conjunction with the photodiode
detectors are discussed above.
[0180] While sensors may share the same LED, photodiode and
excitation/emission filters, in alternative embodiments, separate
LED, photodiode, sensor, and excitation/emission filters may be
employed for each of sensor element and sensing channel. In one
embodiment, Individual sensor elements and sensing channels may
employ different sensing materials, different excitation
wavelengths, and/or different emission wavelengths simultaneously.
While the results provided in Examples 1 through 4 were generated
for array sizes ranging from nine sensor elements to thirty-two
elements, one skilled in the art may increase or decrease both the
size of the sensor array and number of sensing channels, following
the teachings disclosed herein.
[0181] The changes in fluorescence as a result of the odor
interacting with the sensing material is detected by a photodiode
and current to voltage (I/V) converter (FIG. 9) originally designed
by Warner Instruments (Hamden, Conn.) and now commercially
available from Red Shirt Imaging Inc. (Fairfield, Conn.). There is
one I/V converter (FIG. 9) and amplifier/filter (FIG. 10) for each
detector channel. The unique feature of this converter/amplifier
configuration is that when the LEDs are activated prior to sample
delivery, the background fluorescence signal produced by the sensor
elements may be offset by resetting the amplifiers to a baseline
value so that a full range of high gain amplification may be used
to observe small changes in the signals generated by analytes
during sampling. In addition, the innovative amplifier board has
the option for software control to be exerted over the gain and the
filter time constants for all the channels (see connector J2 in
FIG. 12). Thus, in addition to being able to manipulate the onset
and duration of the illumination and of the sniff as described
above, the time constants and gain of the amplifiers can also be
controlled in real time during data acquisition. These hardware
features offer distinct advantages for optimizing the response of
the sensing device for detection, discrimination and identification
of analytes or odors of interest.
F. Electronics--Analytical and Control Circuitry
1. Analytical Circuits
[0182] Generally, the sensing system of the present invention
analyzes spatial-temporal patterns of data output (see FIG. 20)
from sensor arrays in order to characterize and identify the
delivered sample or its analyte components. Useable information
from the sensing array is generated from the pattern of sensor
response activity generated by all sensor elements over time and is
evaluated using statistical measures such as information theory.
Pattern recognition algorithms including template comparison,
neural networks, principal components analysis, etc. may be
implemented either in conventional digital CPUs, in neuronal
network simulator chips, or in analogue neuronal network computers.
Additionally, algorithms based on biologically based neuronal
connections from the olfactory system and other neuronal circuits
in the brain may be employed. The innovative analytical circuits of
the present sensing device provide the requisite hardware support
for the detection, discrimination and identification capability of
the sensing system.
[0183] In one preferred embodiment The circuits comprise current to
voltage converters for each photodiode (FIG. 9) and photodiode
amplification (FIG. 10) with variable gain controlled both manually
and by feedback from the computer (FIG. 12). Amplifiers are reset
after LEDs are switched on to start the data conversion process at
zero volts, as set by a voltage divider on the amplifier output.
This permits both positive and negative differences in fluorescence
to be recorded. Time constants of each amplifier channel are
controlled both manually and by feedback from the computer (FIG.
12). 12 bit, or alternatively, 16 or 24 bit, analogue to digital
(A/D) conversion of signals from each sensing photodiode is
provided. Multiplexing of multiple sensing channels is provided via
the microcontroller computer (FIG. 12).
[0184] FIG. 9 shows a standard current to voltage (I/V) converter
using an Analog Devices AD548 operational amplifier with a choice
of feedback resistors of 1 or 0.5 megohms controlled by a software
switched gate (2N4119) to control the frequency response and noise
properties of the IN board. This circuit converts current changes
in the photodiodes resulting from different levels of light
exposure to voltage changes tht are fed to the amplifier circuit
shown in FIG. 10.
[0185] The standard amplifier circuit in FIG. 10 consists of
operational amplifier transistors (AD548) in circuits which provide
1) a choice of time constants (DC, 500 ms, 100 ms); 2) resetable
baseline; 3) and a choice of gains (1x, 50x, 200x, 1kx). All of
these attributes are under software control via input/output (I/O)
control lines from the computer via the 2N4118 gates. The filter
section of the amplifier is run by a clock line from an oscillator
on the computer control and amplifier control board shown in FIG.
12.
[0186] FIG. 5 shows the circuits to control illumination of the
LEDs. The gate of the MOSFET, IFR510, is controlled by one of the
computer I/O lines under software to turn the LEDs on and off at
the time designated by the program. The LM317 is an adjustable
voltage regulator that determines the voltage delivered to the LED
bank and therefore determines the intensity of the LEDs. The LM317
is controlled by an output digital to analogue line from the
computer under software control.
[0187] FIG. 11 shows how the output lines from the amplifier
channels are connected to the appropriate input lines of the
analogue to digital converters in the microcontroller computer.
There are no active electronic components here, only wired
connections.
[0188] FIG. 12 shows how the I/O lines from connector J2 of the
SmartLCD computer control the various function of the device and
how power is provided to the preamplifier and amplifier boards.
Regulated + and -12 v. and regulated + and -5 v come in through the
main power connector in the upper left of the figure. These
voltages are distributed appropriately to the power connectors for
the preamp and amplifier boards. The J2 connector provides I/O line
control for the MOSFET that controls the LEDs (as described for
FIG. 5) through the `LED/fan` control connector. The inhale and
exhale valves are also controlled by I/O lines going to this
connector. The remaining I/O lines from J2 control the gates (as
described for FIG. 10) that control the time constants, the reset,
and the gains on the amplifier board. The 555 timer generates the
appropriate clock signal (.about.4kHz) for the filters on the
amplifier board. The Siliconix DG442 is simply an intermediate
software controlled switch that interfaces the I/O lines with the
reset line on the amplifier board.
[0189] FIG. 12 shows the interface circuit that allows the
mircocontroller computer to control the LED's, the fan valves
(inhalation and exhalation), the amplifier reset, and the amplifier
gain and time constants from connector J2. As shown in FIG. 4, in
one embodiment, 32 channels are digitized to 12 bits after going
through a voltage divider such that, after the light is turned on
and the amplifiers reset, fluorescence differences in both positive
and negative directions can be detected. The number of sensing
channels may be increased or decreased by replicating or removing
the individual channel circuits shown schematically in FIGS. 4, 5,
9, 10, 11 and 12.
[0190] The device is controlled by a TERN Smart LCD microcontroller
(Tern,lnc., Davis Calif.) computer running at 40 MHz with 512 K
RAM, 66 channels of 12 bit A/D, and programmed in `C` programming
language. In alternative embodiments, a faster computer may be
employed (e.g. PIII-730 with 1 GB RAM) to yield shorter detection
times.
[0191] All electronic parts and circuit components are
conventionally known and readily available at standard electronic
suppliers such as Radio Shack or DigiKey. The I/V (FIG. 9) and
amplifier boards (FIG. 10) were designed and built by Warner
Instruments (Hamden, Conn.) but are made from conventional,
commercially available components from electronic suppliers.
[0192] For the standard electronic parts employed in the described
embodiments there are many interchangeable substitutes which are
known and used in the electronics art. One skilled in the art could
substitute many equivalent programmable microcomputer controllers
as long as they provide a minimum of at least 12 bit or greater
analogue to digital converters, an easy input device (e.g. keypad)
and a simple output device (e.g. LCD display).
III. Sensing Method
A. Overview
[0193] An innovative feature of the present invention is the use of
temporal control over stimulus presentation and the examination of
the resulting changes in sensor output over time. Unlike
conventional designs, with the present invention analyte
presentation to the sensing sites is carried out by negative
pressure `sniffing`, rather than by conventional positive pressure
pulsing which requires samples to be enclosed in confined
containers. An additional innovative feature of the present
invention is that sniffing parameters can be electronically
modulated by feedback from via computer control and flow rate,
sniff duration, and temporal profile can be adjusted and modulated
for specific sampling environments and target analytes to detect
ambient odors drawn into the sensing chamber. Sampling modulations
can be carried out in real time so that subsequent sniffs can be
modified by the preceding ones. With the smart sampling mode
capability of the present invention, a computer turns the sniff on
and off and can modulate and control sniff parameters during a
sampling.
B. Training Runs
[0194] FIGS. 15 and 21 provide schematic flowcharts of typical
training methods employed with the sensing device of the present
invention. Further details of smart mode training are discussed in
later sections and details of one training embodiment are described
in Example 3.
[0195] Target samples of known analytes (odors), either pure
compounds or complex mixtures, are required for training the
sensing device and identifying unknown analytes in sampled fluids.
Training samples are typically provided in small, disposable,
plastic screw top jars which are vapor tight. A small paper cup
insert may be employed with the sample jars as a disposable liner
to facilitate cleaning. For typical target training samples, two
cotton balls are placed in paper cup that is positioned inside the
sample jar and analyte, odor-generating material is typically added
either as a liquid or solid (e.g. camphor, chocolate, cloves, and
orange peels). The cotton provides a high surface area for
promoting evaporation and prevents unrestrained liquid samples from
spilling.
[0196] For all training runs, initially a clean air test sniff is
first taken by initiating the automated sampling sequence which
provides for turning on the LEDs, taking digitized data from the
photodiodes, measuring background fluorescence and storing this in
memory, turning on the sniff pump, turning off the pump,
terminating data acquisition, and turning off the LEDs. The device
is then trained for target analytes by placing the target analyte
sample container into position and initiating the automated
sampling sequence. The sequence of sampling and data acquisition
events for target analytes is the same as for the air baseline
sample. This training sequence is repeated for each target analyte
of interest and response data are stored in the microcontroller
computer RAM memory module.
C. Sampling Runs
[0197] FIGS. 16 and 22 provide schematic flowcharts of typical
sampling procedures employed with the sensing device of the present
invention. Further details of smart mode sampling are discussed in
later sections and details of one sampling method embodiment are
described in Example 3.
[0198] The sequence of steps for sampling analyte-containing fluids
are similar to the training runs described above. A typical
sampling sequence is shown schematically in FIG. 16 and discussed
in more detail in later sections. The entire sampling sequence is
controlled by an microcontroller computer embedded in the sensing
device. The sample timing sequence is, shown in FIG. 14. A typical
sampling run sequence is as follows:
[0199] 1. Set inhalation and exhalation fan valves in partial
exhale mode to prevent uncontrolled diffusion of ambient analytes
into sample chamber.
[0200] 2. LED's are turned on for 100 ms.
[0201] 3. Amplifier baselines are reset while LED's are on (this
zeroes out the background fluorescence).
[0202] 4. LED's turned off
[0203] 5. Wait 150 ms
[0204] 6. Steps 1-3 repeated 5 times to insure amplifier reset is
stable.
[0205] 7. Analyte response run begins
[0206] 8. Turn on LED's for 100 ms
[0207] 9. Take an analog data point from each sensor, convert to
digital value with 12 (0-4095) bit accuracy, place digital value in
memory
[0208] 10. Turn LED's off
[0209] 11. Wait 150 ms
[0210] 12. Repeat steps 8-11 one time (this is before analyte
presentation)
[0211] 13. Switch inhalation valve on and exhalation valve off (see
FIG. 6a)
[0212] 14. Repeat steps 8-11 four times (for 1 sec analyte
pulse)
[0213] 15. Switch inhalation valve off and exhalation valve on (see
FIG. 6b)
[0214] 16. Take 4 more data points (repeating steps 8-11)
[0215] 17. Analyte presentation and data acquisition phases are
complete
[0216] 18. Evaluation circuits and algorithms characterize
spatio-temporal response data of the array either via pattern
recognition algorithms, template matching, a neural network,
statistical analysis, or other analytical methods for analyte
identification
[0217] 19. Results may be displayed on screen, spoken by voice
synthesis, or plotted as a three-dimensional response surface of
fluorescence changes from each sensor at each time point during
sampling. If sensing device is on robotic vehicle, results are
processed for feedback control and decision is made to stay on
course or execute an appropriate maneuver
[0218] Optionally, where multiple samples or complex mixtures
containing multiple analytes are being sampled, the above sampling
steps may be repeated following initiation of the next analyte
application with data sampling and acquisition modifications based
on intelligent feedback via smart algorithms. Thus, real-time,
on-the-fly feedback can dynamically modulate either LED,
photodiode, or sniffing hardware settings, or, alternatively,
analyte sampling parameters such as, sample duration, rise time,
relaxation time, delay from previous sniff, amplifier gain and time
constants may be modified. These modifications may be imposed on
the next data acquisition within the same sampling trial until
detection and identification of the analyte occurs.
D. Data Acquisition
[0219] FIG. 14 shows the timing events for a typical data
acquisition run during sampling. The smart mode features of the
present invention provide for feedback to be applied between or
within single sniffs. The top four traces in FIG. 14 represent
control signals; the bottom three traces represent signals from
three different sensor channels, illustrating different responses
to the same analyte. Upward deflections in the "LED" trace indicate
when the LEDs are turned on. Upward deflections in the "Amp Reset"
trace indicate control pulses sent to the amplifier to reset the
baseline to zero. Thus, the first upward deflection for each sensor
is the response to illumination; resetting the amp brings this
level to zero. When the LEDs turn off, the sensor signal goes to a
negative value (only two amplifier resets are shown here for
simplicity--we typically reset five times). The upward deflections
in the "ADC" (analog-digital conversion) trace indicate when data
points are collected, digitized, and stored in computer memory.
These data points are represented by dots on the sensor traces. The
upward deflection in the "Sniff" trace indicates when inhalation
occurs and analytes reach the sensors. "Sensor 1" shows a slowly
responding sensor that shows an increasing fluorescent signal to a
saturating level with analyte, "Sensor 2" shows a rapidly
responding sensor that quickly saturates, and "Sensor 3" shows a
slowly responding sensor that shows a decreasing fluorescent
signal, but does not saturate.
[0220] As shown in FIG. 14, LEDs are pulsed (LED trace) to reduce
problems with sensor photobleaching. The amplifier reset (Amp Reset
trace) is critical during sampling to providing. zero offset so
that small response signals can still be detected where there is
high background fluorescence. Analog/Digital conversion (ADC trace)
occurs each time data is collected from sensor element channels in
the array. While each sensor element/detector combination within
the array will have temporal response pattern, only response
timings for three sensor channels are shown in FIG. 14. The dots
placed on the sensor response signal schematic indicate times at
which data points are collected The three schematic sensor signals
represent simple examples of possible response types that would
benefit from feedback control. Sensor 1 shows a baseline signal
condition. Sensor 2 shows a rapidly responding sensor signal where
the signal saturates and is clipped with loss of signal
information. With feedback modulation of this sensor during
sampling, subsequent runs may be set to lower amp gain to prevent
signal saturation and data acquisition speed may be increased to
yield more data in the rising portion of the sensor signal. Sensor
3 shows a slowly responding sensor signal. With feedback modulation
of this sensor during sampling, data acquisition speed may be
reduced in subsequent runs to allow the response signal to develop
more fully, yielding a larger signal.
[0221] The steps taken in training the sensor and testing for
analytes, including data analysis and matching, are shown in the
flow charts of FIGS. 15 and 16 and the timing diagram of FIG. 14.
Both FIGS. 15 and 16 represent the steps taken in software. The
"Acquire" steps are the points where the program controls the
hardware to take data as shown in the timing diagram of FIG.
14.
[0222] The software program explicitly controls the pre-bleaching
phase, the duration for which the LED' illuminate the sensors, the
onset of data acquisition, the application of the analyte, the
duration of analyte presentation, the cessation of analyte
application, the duration of the integration time for each data
point, the number of time points, and the interval between time
points. All of these parameters can be modulated either by direct
operator intervention or, alternatively, by programming the
microprocessor with smart algorithms that modify the sampling, data
acquisition, or analysis steps through real-time feedback
control.
E. Data Analysis
[0223] The data are filtered, smoothed, statistically evaluated,
compared with libraries of stored templates for odor
identification,. and/or operated on by any of the algorithms
discussed below. The data are typically stored in memory as an
array of numbers representing the temporal changes in fluorescence
in each sensing channel.
1. Detection Methods and Algorithms
A. Evaluation of Synchrony, Response Signals and Noise
Characteristics
[0224] To improve the detection and discrimination capability of
the sensor of the present invention, additional algorithms may be
employed to evaluate "synchrony" of response data across different
sensor elements to identify small response signals and reject
noise. Evaluation of "synchrony" refers to analyzing how many
signals coming from identical. sensors are similar in the context
of when they occur during the sniff cycle. The field that
encompasses analytical algorithms is very large and many analytical
approaches are available. Due to the innovative features of the
present invention, such as the use of multiple detector channels
with different wavelengths, use of single or multi-pulsed analyte
presentation, and the ability to acquire data from sensor elements
in parallel rather than serially, the design of the present
invention enables consideration of a number of alternative
algorithms beyond those that are conventionally used in artificial
noses. This is what is meant by the term "synchrony". Additionally,
in preferred embodiments algorithms which are based on biological
circuits may be employed [see J. White, et al., Biol. Cybern.
78:245-251(1998); J.White, et al., Anal.Chem. 68(13):2191-2202
(1996); and S. R. Johnson, et al.,Anal.Chem.
69(22):4641-4648(1997), which publications are incorporated herein
by this reference]. The device of the present invention may employ
synchronously occurring signals in some embodiments since sensor
response data are acquired simultaneously in parallel.
B. Detection Algorithms
[0225] The degree to which the response matrix of a test substance
corresponds to one of the target analyte library matrices stored
during the sensor training phase can be evaluated in a number of
ways.
[0226] In one preferred embodiment, a sum of the squared
differences between each value in the test matrix and the training
matrix are generated. These sums may be evaluated by subtracting
the test matrix from all of the stored matrices. The smallest sum
may be used to identify the best target analyte match. This method
was used for the specific embodiments described in Examples
1-4.
[0227] In an alternative preferred embodiment, a supervised, for
example back propagation, neural network approach may be employed.
Examples of these methods are provided in J. White, et al. "Rapid
Analyte Recognition In A Device Based On Optical Sensors And The
Olfactory System", Anal. Chem. 68(13):2191-2202 (1996) and S. R.
Johnson, et al., "Identification Of Multiple Analytes Using An
Optical Sensor Array And Pattern Recognition Neural Networks",
Anal. Chem. 69(22):4641 -4648(1997).
[0228] In another preferred embodiment, analytical circuits based
on the olfactory system may be employed as disclosed by J. White,
et al., "An Olfactory Neuronal Network For Vapor Recognition In An
Artificial Nose", Biol. Cybern. 78:245-251(1998).
[0229] In another preferred embodiment, unsupervised neural
networks may be used. Principle component analysis and
multidimensional scaling are, in effect, unsupervised statistical
methods for reducing dimensionality. Generally, unsupervised neural
networks organize high dimensional input data into lower
dimensional representations. For example, assuming one embodiment
of the present device with 32 sensors and 20 time points, a total
of 640 data points may be collected. In this embodiment, each
analyte presentation can thus be thought of as a point in
640-dimension space, which, while difficult to visualize, may be
mathematically manipulated. By averaging across sensors and time,
the data dimensionality may be reduced, but typically data
dimensionality above about four dimensions is rather difficult to
visualize.
[0230] Self-organizing maps (SOMs) are unsupervised neural networks
that accomplish similar things. Such SOM methods are attractive for
representing artificial olfactory system data because they give a
visualization of "odor space". In other words, a map of
relationships among various analytes can be produced during
training; then during testing, the location of a test analyte on
the `map` indicates the relationship of the analyte with respect to
this `space`. Thus, SOMs may help to visualize relationships among
analytes, rather than simply indicating the similarity of an
unknown analyte to a target. Examples of SOM approaches which may
be particularly useful for analyte detection, discrimination and
identification are disclosed by T. Kohonen. et al., "SOM-PAK: The
Self-Organizing Map Program Package", Report A31, Helsinki
University of Technology, Laboratory of Computer and Information
Science, Espoo, Finland (1996) and T. Kohonen, Self-Organizing
Maps, Series in Information Sciences, Vol. 30, 2.sup.nd ed.,
Springer-Verlag, Heidelberg (1997), which publications are
incorporated herein by this reference.
C. Sampling and Detection Parameter Modulation
[0231] Upon evaluation of the response matrices generated by the
standards used for training, modifications in sniffing parameters,
gain settings, and/or filter settings may be made for actual
sampling of ambient fluids. In a standard operating mode, these
modifications may be made through interventions of an operator who
manually changes sampling and data acquisition parameters through
the programmable microcontroller or by keyboard entry. In
alternative smart operating modes described in subsequent sections,
these modifications may be made automatically, on-the-fly by smart
sampling and detection algorithms that direct mircocontroller
operations.
[0232] Whether and how much such modification improve sensing
performance may be evaluated by examining sensor responses after
feedback and determining, by some predetermined or
analytically-derived criterion, whether current sample data are
better or worse than data obtained on a previous run. Modifications
may also consist of differentially weighting the influence of
sensors, so that those sensors that give the best signals have a
greater impact in the recognition algorithms. This can be done in a
number of ways, such as eliminating sensors that give little or no
signal so as to reduce noise, normalizing the remaining signals to
some standard value in order to use the maximum range available, or
changing analyte sampling and stimulus acquisition paradigm to
optimize sniff sampling parameters.
D. Smart Mode Operation
[0233] Example 3 provides one example of an embodiment of the smart
mode sampling capability of the present invention where the number
and duration of analyte samples taken during a sample session are
controlled by way of real-time feedback and control loops for
improving detection, discrimination and identification of analytes.
In other embodiments, alternative smart mode parameters and device
sampling configurations may be manually or automatically selected
during training and sampling via device menu options. Smart mode
sampling configurations may be used alone or in a variety of
combinations and permutations. In one anticipated embodiment, an
automated training algorithm may be employed to optimize parameter
selection and sampling configuration in order to provide the best
detection and discrimination capability for specific analytes of
interest. Specific examples of alternative smart mode sampling
options and parameter configurations are described below.
1. Sampling Parameters
[0234] A. Sniff parameters.
[0235] i) Sniff duration. This parameter variation is discussed in
Example 3 where significant improvements in detection accuracy are
realized.
[0236] ii) Number of sniffs. In the simplest implementation,
signals across multiple sniffs may be averaged to improve
signal-to-noise. However, different sensors exhibit different
long-term responses to multiple sniffs (providing either increasing
signal, decreasing signal, or constant signal over a series of
sniffs). Monitoring these changes over sniffs (rather than simply
averaging the signals) could provide additional information for
analyte discrimination.
[0237] iii) Sniff dynamics (rise time, fall time). The rate and
extent of sample chamber valves opening and closing may be
controlled to modify sampling (sniff) dynamics. Changing the sniff
dynamics may enhance differences in the rising and falling phases
of the sensor response.
[0238] iv) Sniff velocity. In one anticipated embodiment, a
digital-to-analog line may be used to control a transistor that
could change the voltage supplied to the sniff fan and alter fan
velocity. Changing sniff velocity, in conjunction with changes in
sniff duration, may provide optimized exposure of the sensors to
particular analytes.
[0239] v) Exhalation velocity. As with changing sniff velocity, a
change in exhalation velocity would alter the rate at which analyte
is purged from the sensors and the dynamic sensor response may then
be monitored in subsequent sniffs for improved analyte
discrimination.
[0240] B. LED intensity.
[0241] While higher LED intensity leads to more rapid
photo-bleaching and sensor degradation, it also tends to yield
larger sensor response signals during analyte exposure. In one
smart mode embodiment, normal sampling would be made at lower LED
intensity and, where small response signals are present, LED
intensity may be increased incrementally until reliable response
signals are produced for analyte detection. This smart mode would
tend to extend sensor lifetime by operating at minimum LED
intensity to reduce photobleaching.
[0242] C. LED wavelength.
[0243] The excitation wavelength of the LED may be modulated. LEDs
are commercially available that produce three separate wavelengths.
The wavelength of conventional LEDs may be modulated by changing
applied voltage and flicker frequency. The capability for changing
LED wavelength may permit the device to optimally excite the
sensors and to change that excitation over sniffs to improve
discrimination.
[0244] D. Amplifier gain settings. Under typical sampling
conditions, the highest gain settings are employed. Under such a
condition, some analytes produce sensor signals that saturate the
amplifier. By providing for adjustment of gain settings during
smart mode sampling, if an amplifier channel saturates, an
additional sniff at a lower gain setting Would provide more
accurate time course and amplitude information.
[0245] E. Amplifier temporal filter settings. In general, changing
temporal filter settings may not be entirely straight-forward since
sensor LEDs are typically flashed during sampling to reduce light
exposure. As shown in FIG. 14, data acquisition and A/D conversion
are closely correlated with LED pulse timing. However, since some
detection enhancement may be achieved by modifying the timing of
data acquisition during an LED pulse for improved signal
discrimination for specific analytes, modulation of this parameter
may improve detection and identification of certain analytes.
[0246] F) Gain and temporal filter settings for individual
channels. While one current embodiment of the amplifier electronics
allow manipulation of gain and filter settings globally (i.e. gain
and filter changes apply to all channels simultaneously), in
alternative sensor embodiments, individual sensor channels may also
be manipulated for smart mode sampling and detection.
[0247] Smart mode training and sampling procedures using these and
other parameter variations are discussed in greater detail
below.
[0248] 2. Smart Mode Training
[0249] FIG. 15 provides a schematic flowchart for smart mode
training procedures. Smart mode training is divided into two main
sections: first, the parameters defining the "primary" sniff are
determined, followed by a determination of parameters for any
"secondary" sniff(s) that may be necessary. The constraints for the
two sets of parameters are different: The primary sniffs are
applied at regular intervals over long periods of time and should
have minimum impact on sensor lifetime since they expose the
sensors to as little light as possible to reduce photobleaching and
to as little analyte as possible to prolong sensor lifetime and
shorten recovery time. Secondary sniffs are intended to generate
signals that allow better discrimination to take place.
A. Photobleaching and Bleach Runs
[0250] Exposing a fluorescent sensor to excitation light produces
photobleaching, decreasing the fluorescent output of the sensor.
This fluorescence recovers over time after the excitation light is
turned off. When sensors are exposed to excitation light during
acquisition of response data at variable intervals, there appears
to be more variability in sensor response. Preferably, response
data are acquired at regular intervals within 15 second periods.
Sensor bleach runs establish this regular interval before data are
actually acquired. The bleach runs are repeated until the signals
from the sensors stabilize.
[0251] Bleach runs are acquired without sniffing or taking a
sample. The response matrices from these runs are compared to the
previous run by calculating the sum of squares (SS) difference for
all data points. For the first run, the comparison is to a matrix
of zeroes. If the SS difference is stable, where successive SS
differences change little, training target sampling is initiated.
If the SS difference is unstable, an 15 second inter-run delay time
is used and then the bleach run is repeated. While the operator may
evaluate the SS difference stability visually, this process may be
automated by setting a criterion which provides for minimum changes
in successive SS differences; when that criterion is reached, the
program continues and training target sampling is initiated.
B. Establish Primary Parameters
[0252] Device parameters are initialized to settings that should
give discriminating signals upon analyte exposure. For example, the
LEDs are turned up to the highest intensity by sending the highest
voltage possible out the D/A line (FIG. 3) to the LED controller
(FIG. 5) and a long sniff at high flow is acquired by sending a
voltage signal through the D/A control line (FIG. 3) through an
LM317 circuit to control the inhale servomotor and fan and shown in
FIGS. 3 and 6a. This section of the program finds the minimum
values for these parameters that leads to discrimination of analyte
signals from air. In the flow chart shown in FIG. 15, the
rectangles with rounded corners represent subroutines of several
steps that are described below. The "criterion" referred to here is
initially determined through experimentation with a particular set
of sensors and can be subsequently incorporated into the
programmable microcomputer for automatic control.
[0253] 1. First, sensors that do not respond to any of the analytes
are found. Data from all analytes and air are acquired. For each
sensor, the SS difference between air and each analyte is
calculated. If a sensor does not produce a SS difference value
above criterion for any of the analytes in the training set, that
sensor is removed from consideration for subsequent training and
testing.
[0254] 2. Second, the lowest permissible sniff flow is
determined:
[0255] a) Take single sniffs of all analytes and air.
[0256] b) Calculate SS differences between response matrices of
each analyte and air
[0257] c) If SS difference values are all above a criterion, reduce
sniff flow velocity by 10% (i.e., reduce voltage of D/A by 10%) and
repeat from step 1, otherwise increase flow velocity by 10% (unless
flow is already maximal) and stop.
[0258] d) All data are saved to flash (non-volatile) memory for
possible later use.
[0259] 3. Third, a similar procedure is used to determine the
dimmest LED setting:
[0260] a) Take single sniffs of all analytes and air.
[0261] b) Calculate SS differences between response matrices of
each analyte and air
[0262] c) If SS difference values are all above a criterion, reduce
LED intensity by 10% (i.e., reduce voltage of D/A by 10%) and
repeat from step 1, otherwise, increase LED intensity by 10%
(unless LED intensity is already maximal) and stop.
[0263] d) All data are saved to Flash Memory for potential use
later.
[0264] e) Because the level of excitation light is likely reduced
by the preceding steps, another set of bleach runs is then
taken.
[0265] 4. Fourth, the shortest sniff is determined:
[0266] a) Take single sniffs of all analytes and air.
[0267] b) Calculate SS differences between response matrices of
each analyte and air
[0268] b) If SS difference values are all above a criterion, reduce
sniff duration by half (i.e., open sniff valve for half the time)
and repeat from step 1, else double the sniff duration (unless
sniff duration is already maximal) and stop.
[0269] c) All data are saved to Flash Memory for possible later
use.
[0270] 5. Fifth, the fewest time points to collect is determined.
Start with the short sniff data stored in the previous step (it is
not necessary to collect new data here):
[0271] a) Start by considering data up to the time point just after
the sniff begins.
[0272] b) Calculate SS differences between response matrices of
each analyte and air
[0273] c) If SS difference values are all above a criterion, stop.
Else consider 1 additional time point (unless the number of time
points is already maximal) and repeat from step b.
[0274] d) Because the number of time points to collect is likely
reduced by the preceding steps, another set of bleach runs is
taken.
[0275] The result of the "Establish Primary Parameters" section is
now the lowest flow, dimmest LEDs, shortest sniff, and fewest time
points necessary to discriminate analyte signals from air.
C. Establish Secondary Parameters
[0276] The goal of this section is to determine the parameters of
one or more subsequent sniffs, if necessary, that will improve
discrimination of analytes that are not discriminating based on the
primary sniff alone. The parameter adjustments occur only for the
analytes that are difficult to discriminate. The "criterion"
referred to here is determined through experimentation with the
particular set of sensors used. It may be different from the
criterion used in the primary parameters section above.
[0277] Step 1. Data from all analytes and air are acquired. If this
is the first time through this step, only primary sniffs are
defined and acquired. These data are saved as the primary sniff
targets. The SS differences between each pair of response matrices
is calculated This includes responses to secondary sniffs, if
defined. If all SS difference values are above a criterion, all
targets are deemed to be capable of discrimination. Names are
assigned to the targets and the system is ready for testing (FIG.
16). Otherwise, go to step 2. All of the following steps are
applied only to those analytes that fail to meet the criterion of
step 1.
[0278] Step 2. If the number of sniffs for the "difficult" target
analytes has reached a user-determined maximum, this value will
probably be on the order of 3 or so sniffs, warn the user about the
difficult targets. Assign names to the targets and go to
testing.
[0279] Step 3. Increment the sniff number by 1.
[0280] Each parameter block attempts to optimize the stated
parameter for each of "difficult" targets. The parameter blocks may
be ordered as shown so that the first five parameter modulations do
not increase the amount of excitation light exposure.
[0281] 1. Parameter #1--Difficulty in discrimination may be due to
saturation of the amplifier channel. This is apparent if the signal
from any amplifier channel reaches a value of approx. 2000 or -2000
and stays at that level for 2 or more time points. The Yale
amplifier has gains of 1000.times., 200.times., 50.times., and
1.times.. If saturation occurs, follow the following steps:
[0282] a) Decrease the amplifier gain one step and acquire data
from the difficult targets.
[0283] b) If the SS difference between the difficult targets is now
above criterion, retain this gain setting for these difficult
targets and go to step 1. If the amp gain is at minimum (i.e., none
of the lower amp gains improved discrimination), go to step c.
Otherwise, repeat from step a.
[0284] c) If any of the gain settings produced some improvement,
retain this setting. Otherwise, reset parameter to original value
and go to next parameter block.
[0285] 2. Parameter #2--Since data from longer sniffs may have been
acquired in the "Establish Primary Parameters" section, investigate
those stored data for improved discrimination. If the SS difference
between the difficult targets for any of the longer sniffs is above
criterion, retain the best setting and go to step 1. Else, go to
the next parameter block. If some improvement was made (but still
below criterion), retain the best setting. Otherwise, reset
parameter to original value.
[0286] 3. Parameter #3--Since data from higher sniff velocities may
have been acquired in the "Establish Primary Parameters" section,
investigate those stored data for improved discrimination. If the
SS difference between the difficult targets for any of the higher
sniff velocities is above criterion, retain the best setting and go
to step 1. Else, go to the next parameter block. If some
improvement was made (but still below criterion), retain the best
setting. Otherwise, reset parameter to original value.
[0287] 4. Parameter #4--For a sniff, the valves are normally opened
and closed abruptly (i.e., the PWM signal to the servo changes from
one position to the other instantly). For some analytes and some
sensors, opening and/or closing the valves more slowly may help
produce discriminating signals. To open/close the valves slowly,
the PWM signal to the servos will be changed in smaller steps over
time. In other words, instead of opening the valve fully at a
particular time point, open the valve in two steps over two time
points by opening the valve half way for the first time point, then
fully the next. For an even slower opening, use three steps: open
1/3 at one time point, 2/3 the next, and fully the next. A maximum
of 5 steps will likely be sufficient.
[0288] a) Slow sniff on rate by increasing the number of opening
steps by 1; acquire data from the difficult targets.
[0289] b) If the SS difference between the difficult targets is now
above criterion, retain this sniff setting for these difficult
targets and go to step 1. If the number of sniff steps is at
maximum (i.e., none of the fewer steps improved discrimination), go
to step c. Otherwise, repeat from step a.
[0290] c) Reset number of steps to original value.
[0291] d) Slow sniff off rate by increasing the number of closing
steps by 1; acquire data from the difficult targets.
[0292] e) If the SS difference between the difficult targets is now
above criterion, retain this sniff setting for these difficult
targets and go to step 1. If the number of sniff steps is at
maximum (i.e., none of the fewer steps improved discrimination), go
to step f. Otherwise, repeat from step d.
[0293] f) If any of the sniff on or off settings produced some
improvement, retain the best setting. Otherwise, reset parameters
to original values and go to next parameter block.
[0294] 5. Parameter #5--The amplifier filters are normally set at
DC--no high-pass filtering at all. Adding high-pass filtering may
help to accentuate the rising or falling phases of the sensor
signal, leading to improved discrimination. The filter settings
available on the Yale amplifier have time constants of 500 ms, 100
ms, and 300 ms (increasing the high-pass cut-off frequency). These
values are set using the digital output lines from the Tern
computer (FIG. 3).
[0295] a) Increase the amplifier high-pass cut-off one step and
acquire data from the difficult targets.
[0296] b) If the SS difference between the difficult targets is now
above criterion, retain this filter setting for these difficult
targets and go to step 1. If the filter cut-off is at maximum
(i.e., none of the lower filter settings improved discrimination),
go to step c. Otherwise, repeat from step a.
[0297] c) If any of the filter settings produced some improvement,
retain the best setting. Otherwise, reset parameter to original
value and go to next parameter block.
[0298] 6. Parameter #6--Since data from brighter LEDs may have been
acquired in the "Establish Primary Parameters" section, investigate
those stored data for improved discrimination. If the SS difference
between the difficult targets for any of the brighter LED settings
is above criterion, go to step 1. Otherwise, go to the next
parameter block. If some improvement was made, but it is below the
criterion, retain the best setting. Otherwise, reset parameter to
original value.
[0299] 7. Parameter #7--Since data from more data points may have
been acquired in the "Establish Primary Parameters" section,
investigate those stored data for improved discrimination. If the
SS difference between the difficult targets for any of the
increased data points is above criterion, go to step 1. Otherwise,
go to the next parameter block. If some improvement was made, but
it is below the criterion, retain the best setting. Otherwise,
reset parameter to original value.
[0300] 8. Parameter #8--It is possible that changing exhale
velocity between sniffs may improve signals for the second sniff.
This parameter block is placed last in order to attempt to add to
improvements produced by previous parameter blocks that are still
below criterion.
[0301] a) Decrease exhale velocity by 10% (i.e., decrease voltage
to exhale fan via D/A lines and LM317 voltage controller) and
acquire data from the difficult targets.
[0302] b) If the SS difference between the difficult targets is now
above criterion, retain this velocity setting for these difficult
targets and go to step 1. If the velocity is at minimum (i.e., none
of the lower velocities improved discrimination), go to step c.
Otherwise, repeat from step a.
[0303] c) Reset velocity to original value.
[0304] d) Increase exhale velocity by 10% and acquire data from the
difficult targets.
[0305] e) If the SS difference between the difficult targets is now
above criterion, retain this velocity setting for these difficult
targets and go to step 1. If the velocity is at maximum (i.e., none
of the higher velocities improved discrimination), go to step f.
Otherwise, repeat from step d.
[0306] f) If any of the velocity settings produced some
improvement, retain the best setting. Otherwise, reset parameter to
original value. If the program reaches this point without reaching
criterion, then none of the parameter changes improved
discrimination. Warn the user about the difficult targets, assign
names to the targets, then go to testing.
D. Smart Nose Testing
[0307] FIG. 16 provides a schematic flowchart for smart mode
testing procedures. Smart Nose testing a single analyte can occur
in two stages. First, a primary sniff is taken and, if the primary
sniff produces a good match to a target, that match is reported.
Secondly, if the primary sniff does not produce a good match, one
or more secondary sniff(s), if defined by training, are taken. If a
match criterion is not reached, the matching difficulty is noted
and the closest match reported. If the goodness criterion is
reached, the match is reported.
[0308] 1) Testing begins with parameters determined by "Establish
Primary Parameters" section of training.
[0309] 2) Take bleach runs, as described under Training.
[0310] 3) After an inter-run delay, acquire a primary sniff and
process the data.
[0311] 4) The primary sniff data matrix is matched to the primary
sniff targets by calculating the SS difference to each target (as
described above).
[0312] 5) If "goodness" criterion is reached, report the match.
Continue testing.
[0313] 6) Otherwise, does target with lowest SS difference have
secondary sniff(s) defined? If not, note difficulty, report this
target and continue testing.
[0314] 7) Otherwise, set the appropriate secondary parameters.
[0315] 8) Acquire the secondary sniff(s) and process the data.
[0316] 9) The secondary sniff data matrix (or matrices, if more
than one sniff) is/are matched to the secondary sniff targets by
calculating the SS difference to each target.
[0317] 10) If A "goodness" criterion is reached, report the match.
Otherwise, note difficulty, report closest target, and continue
testing.
E. Sensitivity Improvements and Other Enhancements
[0318] With certain analytes, for example 2, 4 dinitrotuluene
(DNT), which is a major constituent of some explosives, the sensing
system of the present invention has demonstrated very high
sensitivities and detection limits, for example 2-7 parts per
billion (ppb) which are at least an order of magnitude lower than
the best detection limits reported for conventional fiber optic
sensing devices.
[0319] The improved sensitivity, detection and discrimination
capabilities observed with the sensor of the present invention are
due to a number of innovative features. The photodiodes employed in
the present invention are intrinsically more sensitive than and
have larger dynamic range than individual pixels of conventional
CCD camera detectors. The detection surface area of individual
sensor photodiodes in the present device is larger than individual
pixel areas of conventional CCD camera detectors. Additionally, due
to the surface area of the LEDs and photodiodes employed in the
present invention, larger sensor element areas may be employed and
sampling is conducted over a larger geometric surface area of
individual the sensor elements. Furthermore, the innovative liquid
permeable, high porosity high surface area sensor substrates of the
present invention, further enhance sensor response signals due to a
substantial increase in sensor surface area to volume ratios and
the volumetric sampling of sensor response signals generated within
a three-dimensional substrate-sensor volume.
[0320] Another source of increased sensitivity in the present
invention is the capability to reset the baseline of the amplifiers
after turning on the excitation light in order to look only at
fluorescence differences above background, rather than the
background illumination itself. Thus we are not limited by having
to reduce gain or light intensity to prevent detector saturation as
observed with conventional CCD camera detectors. The amplifiers
utilized in the present invention are specifically designed for
resetting signal baseline in order to look at small fluorescence
changes on a large background. In addition, readout from the
photodiodes employed in the present invention is intrinsically
less. noisy than readout from pixels from CCD camera detectors
employed in conventional devices because the readout speed per
channel with the present invention is lower than that of CCD camera
detectors and higher signal-to-noise ratios are achieved.
[0321] The enhanced sensitivity of the present sensor may be
further augmented by utilizing multiple layers of sensing material
`suspended` in the air stream, employing larger surface area sensor
elements and larger surface area photodiodes, and/or using
replicates of multiple identical detectors in the sensor array from
which signals are combined electronically. Replicates of different
sensing materials may be incorporated into different sensor
channels. Using replicates provides advantages not only with
respect to the duplication of data to verify measurement
reproducibility, but also with regard to reducing non-correlated
noise from electronic components such as amplifiers.
EXAMPLES
Example 1
Sensor Response Enhancement
[0322] For evaluating the impact of substrate materials on sensor
response signal enhancement four different sensor substrates were
evaluated including:
[0323] a) a solid glass coverslip; b) a fine tissue paper
(Kimwipe.TM.); c) a porous, low density lens paper; and d) a small
ball of cotton. Four substrates were employed with sensor elements
fabricated from Nile Red dye and polyethylene oxide (PEO) according
to the methods described above. Two substrates were employed with
sensor elements made from a pentiptycene-derived
phenylenecthynylene polymer 1 ("PDPP1") synthesized according to
the method described previously [SeeYang and Swager in
J.Am.Chem.Soc. 120:11864-25 11873(1998), which is incorporated
herein by reference].
[0324] Individual sensor substrate response signals to analyte
vapor were simultaneously measured for each substrate during sample
runs. For PEO-Nile Red sensors, an excitation wavelength of 533 nm,
with a 40 nm band pass, and an emission wavelength of 620 nm, with
a 10 nm band pass, was used. For the PDPP1 sensor measurements,
excitation wavelengths of 460 nm and 430 nm, with a 10 nm band
pass, and emission wavelengths of 488 nm, 500 nm, and 510 nm, with
a 10 nm bandpass were employed.
[0325] FIGS. 17a-d shows sensor response signals to saturated
methanol, amyl acetate, acetone, and dinitrobenzenene analyte
samples for PEO-Nile Red dye polymer applied to various substrates.
FIG. 18 shows sensor response signals to DNT for the PDPP1 polymer
applied to two different substrates. FIGS. 19a-b show sensor
response signals to various concentrations of methanol for PEO-Nile
Red dye polymer applied to two different substrates. Each trace
represents the analyte response with the target air response
subtracted. Thus, each trace shows only the signal due to the
analyte. Each trace is an average of the signals from two sensors
of the same type and from three separate analyte exposures. The
traces are not scaled and the y-axis ranges of each plot are the
same.
[0326] After application of fluorescent dye-polymer materials to
each of the substrates, background fluorescence was measured for
each sample to verify that any observed signal enhancement was not
due to higher background fluorescence. The same excitation and
emission wavelengths used in the response signal measurements shown
in FIGS. 17a-b, 18, and 19a-b were used for background fluorescence
measurements. Voltage measurements were taken from the output of
the amplifiers at a test point between the voltage divider and the
A/D converters. For background fluorescence measurements, LED
intensity was adjusted to a sufficiently low level such that none
of the sensors saturated the amplifier. This intensity was much
lower than that used during the analyte measurements shown in the
plots. For background measurements, the voltages were recorded on a
storage oscilloscope while the LEDs were switched on. These
measurements represent the difference between the amplifier output
before and immediately after the LEDs were turned on before any
significant photo-bleaching occurred. Raw output from detector
amplifiers was measured in volts. Background fluorescence for each
substrate sample were measured as follows:
[0327] Glass--0.325
[0328] Kimwipe.TM.--0.25
[0329] Lens paper--0.275
[0330] Cotton--1.2
[0331] FIGS. 17a-d shows that both Kimwipe.TM. and cotton sensor
substrates produced substantially enhanced response signals
compared to conventional glass substrates. While the background
fluorescence measurements indicate that cotton substrates produces
the highest background fluorescence, as shown in FIGS. 17a-d,
cotton substrate sensor response signals were comparable to
Kimwipe.TM. substrates for methanol analyte and produced the most
enhanced response signals with amyl acetate and dinitrobenzene
analytes. FIG. 18 shows a dramatic signal enhancement for saturated
DNT analyte produced with PDPP1 polymer applied to a Kimwipe.TM.
substrate when compared to glass coverslips. Comparison of the
response signals produced by PEO-Nile Red dye polymer on glass and
Kimwipe.TM. substrates are shown for various concentrations of
methanol analyte samples in FIGS. 19a and 19b. While no enhancement
was observed at dilute concentrations of methanol, a substantial
signal enhancement was observed at higher concentrations of
methanol analyte using the innovative substrates of the present
invention.
Example 2
Analyte Response Characteristics
[0332] As a demonstration of the analyte detection capability of
the sensor of the present invention, eight test samples were
prepared from analyte-saturated air. The target analytes comprised
an air baseline sample, acetone, amyl acetate, carvone, chloroform,
cloves, a commerical cologne (Drakkor Noir.TM.), and
isopropanol.
[0333] For the experiment, a nine element sensor array was
utilized. The methods used for fabrication the sensor elements of
the array are described above and in a previous publication [see J.
White, et al., Anal.Chem. 68(13):2191-2202(1996)]. The sensor
element materials employed in this sensor array are as follows:
1 0 PABS 1 PDPO/Alumina 2 EC 3 Dow 4 PBA 5 PC/Alumina 6 Dow/Alumina
7 PSAN 8 PC PABS = poly(acrylonitrile-butadiene-styrene) Poly
Sciences EC = ethyl cellulose Poly Sciences PBA = poly(1,4-butylene
adipate) Dow = a dimethyl siloxane dispersion coating Dow Corning
PC = polycaprolactone Aldrich PDPO = poly(2.6-dimethyl-1,4
phenylene oxide) Aldrich PSAN = poly styrene-acrylonitrile Poly
Sciences Alumina = 150 mesh alumina Aldrich
[0334] Each analyte sample was sampled for 1 second and data was
taken over a 2.5 sec data acquisition time with data time points
taken every 250 ms. For each analyte, ten samples were measured
over a 2.4 second period. For these experiments, all sensors were
illuminated at an excitation wavelength of 530 nm (40 nm bandpass)
and sensor responses were monitored at an emission wavelength of
620 nm (20 nm bandpass) by application of excitation filters to the
LEDs and emission filters to photodiode detectors.
[0335] FIG. 20 shows typical spatio-temporal response patterns of a
sensor array of the present invention to eight different analyte
samples. Each z-axis value in the matrix represents the magnitude
of fluorescence above or below the baseline at a specific time
point for each specific sensor element. The results shown in FIG.
20 clearly demonstrate the ability of the semi-selective,
cross-reactive sensor array of the present invention to detect and
discriminate among a wide diversity of analytes.
Example 3
Smart Mode Test Results
[0336] To demonstrate one embodiment of the innovative smart mode
sampling, detection, discrimination, and identification capability
of the present invention, the number of samples taken ("sniffs")
and sampling times ("sniff duration") were adjusted and controlled
on-the-fly using real-time feedback obtained from prior sampling
results.
[0337] Since it is generally desirable to provide for sampling at
high frequencies and short durations, the sensing device of the
present invention provides for frequent and rapid environmental
sensing. Two limiting characteristics of dye sensors affect how
frequent and how fast samples can be taken. First, fluorescent
sensors tend to bleach with long exposure to the excitation light,
thereby losing their sensitivity to analytes. Secondly, sensors
tend to yield smaller response signals upon long and frequent
exposure to analyte and some relaxation or recovery time is
generally necessary after such exposure.
[0338] Typically, for frequent sampling, it is preferable to make
the analyte and light exposures brief. However, brief exposures
tend to produce smaller response signals and thus compromise sensor
detection limits. These limitations are overcome by smart mode
sampling where real-time sampling feedback is applied to optimize
sampling time and the number of samples taken. In this mode, short
samples are acquired first, results are checked against a defined
statistical criteria to determine sample validity, and longer
samples are subsequently acquired only where the results of short
sampling are ambiguous or unreliable.
[0339] To demonstrate this particular implementation of the smart
mode sampling capability of the present invention, an eight sensor
array comprising two replicates of four dye-polymer sensors were
employed for discriminating acetone from air. The sensors used for
smart mode sensing are listed below together with their emission
and excitation wavelengths. The cellulose fiber substrate used for
sensors 1-3 was commercial tissue paper sold as Kimwipe.TM.. The
glass fiber substrate used for sensor 4 was a commercial filter
paper sold as MilliPore.TM. Type APFA glass fiber filter (1.6 um
retention/500-500 um thick). These sensors were fabricated
according to the methods described above.
2 #1. Nile Red / Poly(N-vinylpyrrolidone on [ex. 533 nm / em. 600
nm] cellulose fiber substrate #2. Nile Red / Poly(ethylcellulose)
[ex. 533 nm / em. 610] on cellulose fiber substrate #3. Nile Red /
Poly (dimethylsiloxane) [ex. 533 nm / em. 633] on cellulose fiber
substrate #4. Nile Red on a glass fiber substrate [ex. 533 nm / em.
650].
[0340] Prior to actual analyte sampling, the sensor was trained for
the target analytes according to the methods described previously
above. FIG. 21 provides a schematic flowchart of the specific
training steps employed in this experiment. Preliminary target data
were acquired for each sensor in the array by sampling air and
acetone-saturated air for short and long sampling ("sniff")
times.
[0341] The target sampling results for each analyte and each sensor
are provided in FIGS. 23a-d, where responses to both air and
acetone are shown for each sensor for both short and long sample
times (sniffs). For each analyte, five data points were acquired at
100 ms intervals. Sampling duration was 100 ms for short sniffs and
200 ms for long sniffs. The long sniffs were acquired immediately
after the short sniff. It is worth noting that the amplitude of the
second sniff response will recover if a long time interval occurs
between sniffs. The traces shown in the graphs are the average of
two sensor responses for four different runs.
[0342] The target data in FIGS. 23a-d are plotted to clarify the
temporal relationship between short and long sniffs in the training
mode. The horizontal bars toward the bottom of each graph indicate
the duration of the two sniffs with the short sniff being first,
followed about two seconds later by the long sniff. The dotted
lines in the figure depict a two second break in the time axis
between sniffs. The two second delay is the amount of time it takes
for the embedded computer to process the data from the first sniff
and to start up the second sniff. The duration of this delay will
vary with the specific hardware configuration employed. This
interval may be reduced by either converting most of the data
calculations from floating point to integer arithmetic or using a
faster computer. Computational power is not a limiting factor. Note
that the response intensity range of the y-axis are the same for
each figure. The data shown in FIGS. 23a-d are scaled the same way
that the embedded computer scales the data during its processing.
The most significant features of these plots are the relative
signal amplitudes for each analyte and the contribution of each
response signal to analyte discrimination.
[0343] As shown in FIGS. 23a-d, sensor #1 (FIG. 23a) demonstrated
poor discrimination for acetone with short sniff sampling whereas
sensor #2 (FIG. 23b), sensor #3 (FIG. 23c), and sensor #4 (FIG.
23d) show marginally better discrimination with short sniffs. With
longer sniff sampling, sensor #1 shows improved discrimination,
sensor #3 shows marginally similar discrimination and sensors #2
and #4 show dramatically improved discrimination for acetone. In an
ideal sampling application, where sensor element response signals
are large and noise-free, the sampling system would normally
identify target analytes without difficulty. In this example, the
less responsive sensors #1 and #3 were chosen to replicate, in a
controlled manner, a real sampling situation where the sensing
device may become confused due to inconsistent or conflicting
response data obtained from multiple sensors and would make errors
in identification. For these realistic scenarios, the smart mode
sampling would be most useful for detecting, discriminating, and
identifying analytes where response signals are either small and/or
noisy.
[0344] FIG. 22 provides a schematic flowchart of the sampling
procedures used for smart mode sampling in this experiment.
Initially, short sniffs were acquired every 10 seconds. The
measured response was compared to the short sniff targets for air
and acetone using a sum-of-squares matching algorithm that is
described above. Normally, the target with the smaller match score,
or lower sum of least squares, would be reported as the identity of
the test analyte. In the smart sampling mode, all target match
scores, in this case acetone and air, were evaluated to determine
how `good` the match is. If the match was not `good` enough, a
second, longer sniff was acquired and that match was reported. For
detecting target analytes, a `goodness` criterion was applied to
the ratio of the match scores for each analyte. The larger match
score may be evaluated by a criterion wherein it must be some
threshold number of times greater than the smaller match score. Two
examples of this evaluation method is provided below which
demonstrate the improvement in acetone recognition using smart mode
sensing. Following the approach used in signal detection theory,
test matrices are provided in a simplified format which represents
the numbers of hits, misses, false alarms (FA), and correct
rejections (CR): 1
[0345] In each example, fifty sample runs were made, with 25 runs
each of air and acetone. Samples were collected in alternating
blocks of five, five air, then five acetone, then five air, etc.
For a direct comparison, all data were collected in `smart nose`
mode. For the standard mode representation, only the first short
sniff was considered. For the smart mode representation, the final
outcome (whether or not one or two sniffs were acquired) was
considered.
[0346] Example #1:
[0347] a) Standard mode 2
[0348] b) Smart nose mode 3
[0349] In this example, the `goodness` criterion was set to two
(i.e. the ratio of the larger match score to the smaller match
score had to be greater than two). In both modes, the number of
correct rejections (reporting air when air was presented) was high.
The smart sampling mode improved the number of hits (from 48% to
76%). The smart mode evaluation required 18 additional long sniffs
for this improvement.
[0350] Example #2:
[0351] a) Standard Mode 4
[0352] b) Smart nose mode 5
[0353] In this second example, the `goodness` criterion was set to
three. Again, the number of correct rejections was high for both
modes. The more stringent `goodness` criterion improved the number
of hits to 92%, requiring 25 additional long sniffs.
Example 4
[0354] In order to demonstrate the unique sensitivity, detection,
and discrimination capabilities of the sensor of the present
invention, five vapor mixtures of analyte-saturated air were
sampled with a nine element sensor array of the present invention
and a sixteen element fiber optic sensor array for comparing the
relative sensitivity and discriminating capability of the two
sensing devices. Table 4.1 lists the sensor element types employed
for each sensor array in the comparative testing. These sensors
were fabricated according to the methods described above. The
fabrication methods employed for the sensor elements and fiber
optic sensor device are described previously [see J. White, et al.,
Anal. Chem. 68(1 3):2191 -2202(1996)].
[0355] The response of the fiber optic sensing device to air,
methanol, amyl acetate, acetyl acetate, and xylene analytes was
initially evaluated using a CCD camera detection system and an
enclosed, positive pressure, sample delivery method described
previously (see J. White, et al., Anal. Chem. 68:2191-2202 (1996)).
During sampling, the CCD gain was adjusted such that non-saturating
signals were obtained from all sensors in the fiber optic array.
The maximum gain which would provide detectable responses from less
responsive sensors and not saturate the CCD amplifier with highly
response sensors was utilized. Unlike the present invention, the
fiber optic sensor employs a CCD camera detector that does not
provide for adjusting the gain for each sensor element based on the
sensor element response signal. This is an undesirable limitation
in individual sensor response capabilities since the response
signal for each sensor element in the array can not be optimized
with this device. In contrast, the present sensing device has the
capability for adjusting the gain of individual sensor channels to
obtain maximum response signal from each sensor in the array. Such
a capability is particularly advantageous when there is a
significant difference in the response signals of sensor array
elements to specific analytes. By providing for gain adjustment of
individual sensor channels, optimum detection, discrimination, and
sensor response utilization is achieved by optimizing signal
response intensity and signal to noise ratios for each sensor
element in the array. This capability for individually adjusting
sensor element response signal is essentially impossible to achieve
with the conventional CCD camera detectors that are typically
employed with fiber optic sensors.
3TABLE 4.1 Sensor Elements Employed for Comparative Performance
Testing Element No. Present Invention Element No. Fiber Optic
Sensor 7 Dow/alumina 2 background - no polymer 4 Dow 3 PS802/20%
MMA 1 PABS 4 cellulose/alumina/ cellulose 8 PSAN 5 RMS-044/ 20% MMA
5 PBA 6 (inoperative) 2 PDPO/alumina 7 Dow/alumina 9 PC 8
Dow/alumina/ PDPO 6 PC/alumina 9 P5802/PS901.5 3 EC 10 P5802/10%
MMA 11 PDPO 12 Dow (2 dips) 13 RMS-044 14 PS901.5 15 PS802 16
Dow/alumina/Dow 17 Dow(Sdips) 18 (inoperative) 19 PC/PSAN/alumina
20 (inoperative) 21 cellulose/PDPO and beads Abbreviations DOW = a
dimethyl siloxane dispersion coating PC = polycaprolactone PDPO =
poly(2.6-dimethyl-1.4 phenylene oxide) PSAN = poly
styrene-acrylonitrile Cellulose = ethyl cellulose MMA = methyl
methacrylate PS802 = (80-85% di methyl (15-20%) acryloxypropyl)
Methylsiloxane copolymer PS901.5 = poly (acryloxypropylmethyl)
siloxane RMS-044 = 4-6% (methacryloxypropyl) methyl-siloxane,
dimethyl siloxane copolymer PBA = poly (1,4-butylene adipate)
Supplier DOW Corning Aldrich Aldrich Poly Sciences Poly Sciences
Aldrich United Chemical Technologies United Chemical Technologies
United Chemical Technologies
[0356] While initial sampling tests with the fiber optic sensor
employed an enclosed, positive pressure chamber that contained
analyte vapors, in order to make a direct comparison of the sensing
performance of the two sensing devices, a small port hole was
drilled into the sample chamber area of the present invention for
positioning the fiber optic sensor. With this configuration,
response measurements for both sensing devices could be directly
compared using the same analyte sampling pulse generated by the
sampling valves and fans of the present invention.
[0357] Data were acquired from both the fiber optic sensor and the
present sensor while introducing odors to the sample chamber via
the valve and fan assembly of the present invention. In this
manner, the difference in sensitivity between the two sensors to
pulses of analyte generated by the same odor delivery method could
be monitored. To avoid interference during data acquisition for
each sensing device, the fiber optic sensor excitation light source
was turned off when acquiring data from the present sensor and the
LED excitation light sources were turned off when acquiring data
from the fiber optic sensor . Both sensing devices employed the
same sensor excitation wavelength of 530 nm (40 nm bandpass) and
same sensor emission wavelength of 620 nm (20 nm bandpass) by
applying excitation filters to the light source and emission
filters to the detection means for each sensing device.
[0358] In comparing the fiber optic sensor response to methanol
during initial testing, the amplitude of the fiber optic signal
obtained within the sample chamber was generally about half the
amplitude of the signal obtained using an enclosed, positive
pressure sampling container which is typically used when making
sample measurements with this device. While reduced response signal
could be overcome by increasing detector gain settings, this was
not possible with the fiber optic sensor since the CCD amplifier
was set at the maximum permissible gain which would avoid CCD
detector saturation from the high fluorescence background of the
sensor elements. In contrast, the sensor of the present invention
produced a much larger response signal to the same methanol analyte
pulse. Although very large response signals may saturate the
amplifier of the present sensor, it is still possible to use the
full range of the A/D conversion for all the sensors in the present
array since the baseline intensities for every sensors may be reset
to a common value.
[0359] For the plots shown in FIGS. 24a-b, 24d, 25a-b, and 26a-c a
full-scale y-axis plotting range of 4000 response intensity units
was used for displaying the signal response for as a function of
time for both sensing devices. This scale approximated the
resolution limit for sensor response measurements since all data
were digitized to 12 bits which resulted in response data values
ranging from 0 to 4096 for both devices. For the fiber optic
sensor, data are plotted as pixel values and for the present
sensor, data are plotted as fluorescence analog/digital values. For
the plots shown in FIGS. 24c, 24e, and 25c-d, due to the low
response signals produced by the fiber optic sensors, a much
smaller range is plotted which shows much lower signal changes than
the data obtained with the present invention plotted at full scale
in FIGS. 26a-c. Due to the typically slower sensor response times
observed with the fiber optic sensor, measurements were made over a
20 second time frame for this device whereas a 5 second measurement
period was used for the present invention. In comparing sensing
performance of the two sensor devices, the most important parameter
is the relative amplitude of the signals obtained for individual
sensor elements in response to analytes.
[0360] Since, as discussed above, the baseline signal for
individual fiber optic sensor elements could not be reset to avoid
saturation, the video gain for the fiber optic sensor measurements
was set at the maximum gain that prevented the brightest sensors
from saturating the CCD. This led to a compromise in response
signal response for sensors in the fiber optic array since signal
gain for individual sensors could not be adjusted for maximum
sensitivity and resolution. Thus, response signals from sensors
producing low signal could not be amplified without saturating high
signal producing sensors and response signals from sensors
producing high signal could not be reduced without risking loss of
signal from less responsive sensors. In contrast, since the sensor
of the present invention has the capability to both reset response
baselines for all sensors in the array and then maximize sensor
gain for all sensors, the sensor of the present invention provided
much higher response signal, resolution and sensitivity for optimum
sensor response to analytes.
[0361] In FIGS. 24a-e, the sensor responses for two sensor elements
of the fiber optic sensor, a cellulose-alumina sensor and a Dow
sensor, are shown for a methanol-saturated analyte sample and a
1:10 dilution of this analyte sample. The compositions and methods
for fabricating these sensors are described above. The
cellulose-alumina sensor data represents the most responsive (i.e.
bright) sensor observed for methanol with the fiber optic devices
while the Dow sensor data represents a typical, moderately
responsive (i.e. less bright) sensor. In FIG. 24a, the upper pixel
intensity trace is from the bright sensor and the lower trace from
the less bright sensor. This plot shows a substantial difference in
intensity for the two sensors such that the gain of the Dow sensor
cannot be increased without saturating the cellulose-alumina
sensor, resulting in the loss of sensor reliability. The full-scale
plot of FIG. 24b shows the minimal change in pixel intensity of the
less bright Dow sensor upon exposure to methanol as either a
saturated analyte sample or a 1:10 sample dilution. These data are
replotted in FIG. 24c on a much finer scale and clearly shows the
relatively low response signal of this sensor to methanol where a
saturated analyte sample produces only about 40 pixel intensity
unit change, or 1% of full-scale, while a dilute analyte sample
produces only about a 15 unit change, or about 0.4% of full-scale.
The full-scale plot of FIG. 24d shows the relatively modest change
in pixel intensity of the bright cellulose-alumina sensor upon
exposure to saturated methanol analyte solution and a diluted
sample solution. These data are replotted in FIG. 24e on a finer
scale and show a modest 200 unit increase in intensity, or 5% of
full-scale, for the saturated analyte, and less than a 50 unit
change, or about 1 % change of full-scale, for the dilute analyte
sample. In dramatic contrast to the fiber optic sensor response
measurements, the increased sensitivity, resolution, and detection
capability of the innovative sensor of the present invention to
saturated methanol and dilute methanol analyte samples is shown in
FIG. 26a where data for the less bright Dow sensor material are
provided. With the present sensor, the dilute analyte exhibits
about a 1100 unit change in intensity, or 25% of full-scale whereas
the saturated analyte shows over a 1700 unit change in intensity,
or about 43% of full-scale. With the fiber optic device, the,
equivalent sensor material produced only from 1 to 10% of the
signal of the present invention in response to the same analyte
solutions.
[0362] Similar results were observed with other analyte samples.
FIGS. 25a-b show the minimal pixel intensity change of the fiber
optic device to saturated and diluted amyl acetate analyte
solutions where a change of only 27 to 38 intensity units was
observed with the Dow sensor element. In contrast, FIG. 26b shows
the significant intensity change of the present sensor device to
saturated and diluted amyl acetate sample solutions where a change
of 500 to 1000 intensity units was observed with the Dow sensor
element. The fiber optic device apparently produced only 3-5% of
the signal of the present invention in response to the same analyte
solutions. FIGS. 25c-d show that the fiber optic device has an
extremely low responsivity to saturated and diluted xylene analyte
solutions where the response signal is relatively noisy and a
change of only about three intensity units is observed for each
analyte sample. In contrast, FIG. 26c shows the significant
intensity change of the present sensor device to saturated and
diluted xylene sample solutions where a change of about 50-250
intensity units was observed with the Dow sensor element in
response to the dilute and concentrated analytes. The fiber optic
device apparently produced only 1-4% of the signal of the present
invention in response to the same analyte solutions.
[0363] These results demonstrate that the response signal
amplitude, resolution, sensitivity, detection and discrimination
capability that can be achieved with the innovative sensor of the
present invention is substantially better than even the largest
signal obtained from the most responsive sensor materials with
fiber optic sensor devices. These data unambiguously demonstrate
the enhanced detection and discrimination capability of the sensor
of the present invention which provides for high signal to noise,
increased sensitivity, lower detection and identification limits
and greater discrimination in analyte sensing. In addition, from
these results, it appears that the response time of the innovative
sensor of the present invention is significantly faster than fiber
optic sensor devices.
[0364] The ability to reset the amplifier in the device of the
present invention provides the capability to sense from all sensors
in the array simultaneously without compromising signal information
from either the most responsive or least responsive elements in the
array. Furthermore, this innovative feature of the sensor of the
present inventions enables use of higher gain settings and reduced
noise, resulting in larger response signals and improved analyte
detection and discrimination capability. These response measurement
results clearly demonstrate the unique and advantageous
sensitivity, detection limits, and discrimination capabilities of
the device of the present invention when compared to conventional
sensor designs under the same test conditions.
[0365] Having described the preferred embodiments of the invention,
it will now become apparent to one of skill in the art that other
embodiments incorporating the concepts may be
* * * * *