U.S. patent application number 15/885444 was filed with the patent office on 2018-07-26 for optical patient monitor.
The applicant listed for this patent is MASIMO CORPORATION. Invention is credited to Ammar Al-Ali.
Application Number | 20180206795 15/885444 |
Document ID | / |
Family ID | 39676760 |
Filed Date | 2018-07-26 |
United States Patent
Application |
20180206795 |
Kind Code |
A1 |
Al-Ali; Ammar |
July 26, 2018 |
OPTICAL PATIENT MONITOR
Abstract
An optical based patient monitoring system employing an optical
sensor and providing an indication of an optical change which does
not correlate to a change in a physiological blood parameter and
based on that indication, providing a care provider an indication
of a condition of a patient. The optical based patient monitoring
system providing the indication of the patient condition in
relation to a patient using an IV setup.
Inventors: |
Al-Ali; Ammar; (San Juan
Capistrano, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MASIMO CORPORATION |
Irvine |
CA |
US |
|
|
Family ID: |
39676760 |
Appl. No.: |
15/885444 |
Filed: |
January 31, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
15862283 |
Jan 4, 2018 |
|
|
|
15885444 |
|
|
|
|
14507415 |
Oct 6, 2014 |
|
|
|
15862283 |
|
|
|
|
11963640 |
Dec 21, 2007 |
8852094 |
|
|
14507415 |
|
|
|
|
60876749 |
Dec 22, 2006 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/7405 20130101;
A61B 5/7246 20130101; A61B 5/021 20130101; A61B 5/6838 20130101;
A61B 5/7275 20130101; A61B 5/14551 20130101; A61B 5/4839 20130101;
A61B 5/14546 20130101; A61B 5/0004 20130101; A61B 5/7221 20130101;
A61B 5/0205 20130101; A61B 2560/0443 20130101; G16H 50/30 20180101;
A61B 5/14532 20130101; A61B 5/024 20130101; A61B 5/14539 20130101;
A61B 5/7282 20130101; A61B 2560/0285 20130101; A61B 5/082 20130101;
A61B 5/0402 20130101; A61B 5/08 20130101; A61B 5/14552 20130101;
A61B 2562/222 20130101; A61B 5/412 20130101; A61B 5/742 20130101;
A61B 5/1455 20130101; A61B 5/6826 20130101; A61B 5/6832 20130101;
A61B 5/6843 20130101; G16H 40/63 20180101; A61B 5/01 20130101; A61B
5/0816 20130101; A61B 5/746 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 5/145 20060101 A61B005/145; A61B 5/1455 20060101
A61B005/1455 |
Claims
1. A system which uses a light emitter and an optical detector to
determine a condition of a patient and electronically transmit an
audio or visual indication to alert a care provider about the
condition of the patient, the system comprising: a first disposable
adhesive attachment component, utilizing an adhesive attachment
mechanism, configured to attach to a measurement site of the
patient; a reusable component including a light emitter and a light
detector, the reusable component configured to attach to the first
disposable adhesive attachment component, the reusable component
configured to emit at least a plurality of wavelengths of light
into a portion of the patient's body and detect the emitted light
reflected from the patient; a processor configured to monitor a
characteristic of the patient to determine the condition of the
patient, the processor configured to process the detected light to
determine a change in a magnitude of the detected light which does
not correlate to a change in a physiological blood parameter,
wherein based on the processing, the processor also determines if
the condition affecting the patient should be communicated to a
healthcare provider; and a display device configured to
communicating the condition affecting the patient to a care
provider using either an audio or visual indication.
2. The system of claim 1, wherein the condition is one of a probe
off condition, change or presence of a therapeutic drug or
perfusion condition.
3. The system of claim 1, wherein the condition is a movement of
the reusable component from the measurement site to a second
different measurement site.
4. The system of claim 1, wherein the change in the magnitude of
the detected light which does not correlate to a change in a
physiological blood parameter is a movement of the reusable
component from the measurement site to a second different
measurement site.
5. The system of claim 1, wherein the system is configured to be
used in conjunction with an IV setup and the processor is
configured to monitor the characteristic of the patient related to
an infusion of the IV setup.
6. A system which electronically transmits a signal indicative of a
patient condition from a measurement location to a processing
device, the system comprising: a first disposable adhesive
attachment component, utilizing an adhesive attachment mechanism,
configured to attach to a measurement site of the patient; a
reusable component including a light emitter and a light detector,
the reusable component configured to attach to the first disposable
adhesive attachment component, the reusable component configured to
emit at least a plurality of wavelengths of light into a portion of
the patient's body and receive the emitted light reflected from the
patient; a cable configured to transmit the signal from the patient
measurement site to a patient monitor the patient monitor including
a processor configured to process an indication of the detected
light to determine a change in the normalized magnitudes of the
detected light which does not correlate to a change in a
physiological blood parameter to determine the patient
condition.
7. The system of claim 6, wherein the condition is a probe off
condition.
8. The system of claim 6, wherein the condition is change or
presence of a therapeutic drug.
9. The system of claim 6, wherein the condition is a perfusion
condition.
10. The system of claim 6, wherein the condition is a movement of
the reusable component from the measurement site to a second
measurement site.
11. The system of claim 6, wherein the system is configured to be
used in conjunction with an IV setup and the processor is
configured to determine the patient condition responsive to an
infusion of the IV setup.
12. The system of claim 6, wherein the blood parameter is
methemoglobin.
13. The system of claim 6, wherein processor is further configured
to prevent an alarm condition where the processed indication of the
detected light to determine a change in the normalized magnitudes
of the detected light which does not correlate to a change in a
physiological blood parameter indicates that a change in a
measurement of a physiological blood parameter is not due to an
actual physiological change in the blood.
14. A method of detecting a change in light absorption
characteristics at a measurement site of a patient, the change
being unrelated to a physiological blood parameter of a patient,
the method comprising: providing a first disposable adhesive
attachment component, the first disposable adhesive attachment
component having an adhesive attachment mechanism and configured to
attach to a measurement site of a patient; providing a second
reusable component configured to couple to the first disposable
adhesive attachment component, the reusable component configured to
emit at least a plurality of wavelengths of light into a portion of
the patient's body and receive the emitted light reflected from the
patient; and determining, using a hardware processor a condition
affecting the patient based on the received light reflected from
the patient; determining, using the hardware processor that a
change in light absorption has occurred that is not related to a
change in a composition of arterial blood of the patient; providing
an indication alerting a care provider of a condition of a
patient.
15. The method of claim 14, wherein the condition is a probe off
condition.
16. The method of claim 14, wherein the condition is a change or
presence of a therapeutic drug.
17. The method of claim 14, wherein the condition is a perfusion
condition.
18. The method of claim 14, wherein the condition is a movement of
the reusable component from the measurement site to a second
measurement site.
19. The method of claim 14, wherein the condition is responsive to
an infusion of the IV setup.
20. A system which uses a light emitter and an optical detector to
determine a condition of a patient and electronically transmit an
audio or visual indication to alert a care provider about the
condition of the patient, the system comprising: a first disposable
adhesive attachment component, utilizing an adhesive attachment
mechanism, configured to attach to a measurement site of the
patient; a reusable component including a light emitter and a light
detector, the reusable component configured to attach to the first
disposable adhesive attachment component, the reusable component
configured to emit at least a plurality of wavelengths of light
into a portion of the patient's body and detect the emitted light
reflected from the patient; a processor configured to monitor a
characteristic of the patient to determine the condition of the
patient, the processor configured to process the detected light to
determine a change in a magnitude of the detected light which does
not correlate to a change in a physiological blood parameter; and a
display device configured to communicate the condition affecting
the patient to a care provider using either an audio or visual
indication.
21. The system of claim 20, wherein the condition a probe off
condition.
22. The system of claim 20, wherein the condition is a presence of
a therapeutic drug.
23. The system of claim 20, wherein the condition a perfusion
condition.
24. The system of claim 20, wherein the condition is a movement of
the reusable component from the measurement site to a second
different measurement site.
25. The system of claim 20, wherein the change in the magnitude of
the detected light which does not correlate to a change in a
physiological blood parameter is a movement of the reusable
component from the measurement site to a second different
measurement site.
26. The system of claim 20, wherein the system is configured to be
used in conjunction with an IV setup and the processor is
configured to monitor the characteristic of the patient related to
an infusion of the IV setup.
Description
PRIORITY CLAIM TO RELATED PROVISIONAL APPLICATIONS
[0001] Any and all applications for which a foreign or domestic
priority claim is identified in the Application Data Sheet are
hereby incorporated by reference under 37 CFR 1.57.
FIELD OF THE DISCLOSURE
[0002] The present disclosure relates to a sensor for measuring
physiological parameters and, in particular, relates to using
measured physiological parameters to generate an indicator.
BACKGROUND
[0003] Pulse oximetry is a widely accepted noninvasive procedure
for measuring the oxygen saturation level of arterial blood, an
indicator of a person's oxygen supply. Early detection of a low
blood oxygen level is critical in the medical field, for example in
critical care and surgical applications, because an insufficient
supply of oxygen can result in brain damage and death in a matter
of minutes. A typical pulse oximetry system utilizes a sensor
applied to a patient's finger. The sensor has an emitter configured
with both red and infrared LEDs that project light through the
finger to a detector so as to determine the ratio of oxygenated and
deoxygenated hemoglobin light absorption. In particular, the
detector generates first and second intensity signals responsive to
the red and IR wavelengths emitted by the LEDs after absorption by
constituents of pulsatile blood flowing within a fleshy medium,
such as a finger tip. A pulse oximetry sensor is described in U.S.
Pat. No. 6,088,607 titled Low Noise Optical Probe, which is
assigned to Masimo Corporation, Irvine, Calif. and incorporated by
reference herein.
[0004] Capnography comprises the continuous analysis and recording
of carbon dioxide concentrations in the respiratory gases of
patients. The device used to measure the CO.sub.2 concentrations is
referred to as a capnometer. CO.sub.2 monitoring can be performed
on both intubated and non-intubated patients. With non-intubated
patients, a nasal cannula is used. Capnography helps to identify
situations that can lead to hypoxia if uncorrected. Moreover, it
also helps in the swift differential diagnosis of hypoxia before
hypoxia can lead to irreversible brain damage. Pulse oximetry is a
direct monitor of the oxygenation status of a patient. Capnography,
on the other hand, is an indirect monitor that helps in the
differential diagnosis of hypoxia so as to enable remedial measures
to be taken expeditiously before hypoxia results in an irreversible
brain damage.
[0005] Early detection of low blood oxygen is critical in a wide
variety of medical applications. For example, when a patient
receives an insufficient supply of oxygen in critical care and
surgical applications, brain damage and death can result in just a
matter of minutes. Because of this danger, the medical industry
developed pulse oximetry, a noninvasive procedure for measuring the
oxygen saturation of the blood. A pulse oximeter interprets signals
from a sensor attached to a patient in order to determine that
patient's blood oxygen saturation.
[0006] A conventional pulse oximetry sensor has a red emitter, an
infrared emitter, and a photodiode detector. The sensor is
typically attached to a patient's finger, earlobe, or foot. For a
finger, the sensor is configured so that the emitters project light
from one side of the finger, through the outer tissue of the
finger, and into the blood vessels and capillaries contained
inside. The photodiode is positioned at the opposite side of the
finger to detect the emitted light as it emerges from the outer
tissues of the finger. The photodiode generates a signal based on
the emitted light and relays that signal to the pulse oximeter. The
pulse oximeter determines blood oxygen saturation by computing the
differential absorption by the arterial blood of the two
wavelengths (red and infrared) emitted by the sensor.
SUMMARY
[0007] Multiple physiological parameters, combined, provide a more
powerful patient condition assessment tool than when any
physiological parameter is used by itself. For example, a
combination of parameters can provide greater confidence if an
alarm condition is occurring. More importantly, such a combination
can be used to give an early warning of a slowly deteriorating
patient condition as compared to any single parameter threshold,
which may not indicate such a condition for many minutes.
Conditions such as hypovolemia, hypotension, and airway obstruction
may develop slowly over time. A physiological parameter system that
combines multiple parameters so as to provide an early warning
could have a major effect on the morbidity and mortality outcome in
such cases. Parameters can include ECG, EKG, blood pressure,
temperature, SpO.sub.2, pulse rate, HbCO, HbMet, Hbt, SpaO2, HbO2,
Hb, blood glucose, water, the presence or absence of therapeutic
drugs (aspirin, dapson, nitrates, or the like) or abusive drugs
(methamphetamine, alcohol, or the like), concentrations of carbon
dioxide ("CO2"), oxygen ("O"), ph levels, bilirubin, perfusion
quality, signal quality, albumin, cyanmethemoglobin, and
sulfhemoglobin ("HbSulf") respiratory rate, inspiratory time,
expiratory time, inspiratory to expiratory ratio, inspiratory flow,
expiratory flow, tidal volume, minute volume, apnea duration,
breath sounds--including rales, rhonchi, or stridor, changes in
breath sounds, heart rate, heart sounds--including S1, S2, S3, S4,
or murmurs, or changes in heart sounds, or the like. Some
references that have common shorthand designations are referenced
through such shorthand designations. For example, as used herein,
HbCO designates carboxyhemoglobin, HbMet designates Methemoglobin,
and Hbt designates total hemoglobin. Other shorthand designations
such as COHb, MetHb, and tHb are also common in the art for these
same constituents. These constituents are generally reported in
terms of a percentage, often referred to as saturation, relative
concentration or fractional saturation. Total hemoglobin is
generally reported as a concentration in g/dL. The use of the
particular shorthand designators presented in this application does
not restrict the term to any particular manner in which the
designated constituent is reported.
[0008] Further, a greater emphasis has been put on decreasing the
pain level of patients on the ward. Accordingly, patients are often
given an IV setup that enables the patient to increase the level of
analgesia at will. In certain situations, however, the patient's
input must be ignored so as to avoid over medication. Complications
from over sedation may include hypotension, tachycardia,
bradycardia, hypoventilation and apnea. A physiological parameter
system that uses pulse oximetry monitoring of SpO.sub.2 and pulse
rate in conjunction with patient controlled analgesia (PCA) can aid
in patient safety. Utilization of conventional pulse oximetry in
conjunction with PCA, however, can result in the patient being
erroneously denied pain medication. Conventional monitors are
susceptible to patient motion, which is likely to increase with
rising pain. Further, conventional monitors do not provide an
indication of output reliability.
[0009] Advanced pulse oximetry is motion tolerant and also provides
one or more indications of signal quality or data confidence. These
indicators can be used as arbitrators in decision algorithms for
adjusting the PCA administration and sedation monitoring. Further,
advanced pulse oximetry can provide parameters in addition to
oxygen saturation and pulse rate, such as perfusion index (PI). For
example, hypotension can be assessed by changes in PI, which may be
associated with changes in pulse rate. Motion tolerant pulse
oximetry is described in U.S. Pat. No. 6,206,830 titled Signal
Processing Apparatus and Method; signal quality and data confidence
indicators are described in U.S. Pat. No. 6,684,090 titled Pulse
Oximetry Data Confidence Indicator, both of which are assigned to
Masimo Corporation, Irvine, Calif. and incorporated by reference
herein.
[0010] One aspect of a physiological parameter system is a first
parameter input responsive to a first physiological sensor and a
second parameter input responsive to a second physiological sensor.
A processor is adapted to combine the parameters and predetermined
limits for the parameters so as to generate an indication of
wellness.
[0011] Another aspect of a physiological parameter system is a
parameter input responsive to a physiological sensor and a quality
indicator input relating to confidence in the parameter input. A
processor is adapted to combine the parameter input, the quality
indicator input and predetermined limits for the parameter input
and the quality indicator input so as to generate a control
output.
[0012] A physiological parameter method comprises the steps of
inputting a parameter responsive to a physiological sensor and
inputting a quality indicator related to data confidence for the
parameter. A control signal is output from the combination of the
parameter and the quality indicator. The control signal is adapted
to affect the operation of a medical-related device.
[0013] A method of improving the reporting of a physiological
parameter in a physiological parameter system comprises obtaining
measurements of a physiological parameter from a measurement site.
At least some of the physiological parameter measurements are
maintained. A change in the measurement site is detected. A
measurement of the physiological parameter from a new measurement
site is obtained. The measurement of the physiological parameter at
the new measurement site is compared with the maintained
physiological parameter measurements. The magnitude of the
physiological parameter reported by the physiological parameter
system at the new measurement site is adjusted to approximately
match the magnitude of the maintained physiological parameter
measurements.
[0014] A method of generating an indicator of patient wellness
using a physiological parameter system includes receiving
physiological parameter data from a sensor attached to the
physiological parameter system. Physiological parameter preferences
are provided to the physiological parameter system. The
physiological parameter data is compared to the physiological
parameter preferences. An indicator of patient wellness is
generated by calculating a numerical wellness score based on the
comparison.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] FIG. 1 illustrates an embodiment of a physiological
parameter measurement system.
[0016] FIG. 2A illustrates an embodiment of a sensor assembly.
[0017] FIGS. 2B-C illustrate alternative sensor embodiments.
[0018] FIG. 3A illustrates an example chart of the value of a
physiological parameter as measured by a sensor during a time when
the sensor is moved from one measurement site to another.
[0019] FIG. 3B illustrates a chart of a physiological parameter
reported by a measurement system employing signal normalization
techniques.
[0020] FIG. 3C illustrates a chart of a MetHb reading which is
smoothed to account for abnormal variations in the readings.
[0021] FIG. 3D illustrates a MetHb smoothing flowchart.
[0022] FIG. 3E illustrates a system of multiple different MetHb
calculators which determine MetHb using different methods in order
to calculate the most accurate MetHb reading.
[0023] FIG. 4 is a block diagram of a physiological parameter
system having signal normalization capability.
[0024] FIG. 5 illustrates an embodiment of a method for normalizing
a signal acquired by a sensor.
[0025] FIG. 6 is a general block diagram of a physiological
parameter system having alarm, diagnostic and control outputs.
[0026] FIG. 6A illustrates an embodiment of a physiological
parameter system 600 similar to the system in FIG. 6.
[0027] FIG. 7 is a block diagram of a physiological parameter
system combining pulse oximetry and capnography and providing alarm
outputs.
[0028] FIG. 8 is a block diagram of a saturation limit alarm
enhanced by ETCO.sub.2 measurements.
[0029] FIG. 9 is a block diagram of a CO.sub.2 waveform alarm
enhanced by SpO.sub.2 measurements.
[0030] FIG. 10 is a block diagram of a physiological parameter
system combining pulse oximetry and capnography and providing a
diagnostic output.
[0031] FIGS. 11A, 11B, 12 are block diagrams of a physiological
parameter system utilizing pulse oximetry to control patient
controlled analgesia (PCA).
[0032] FIGS. 13, 13A, 13B illustrates an embodiment of a system
that displays an indicator of the wellness of a patient.
[0033] FIG. 14 is a flowchart showing an example method of
displaying an indicator of the wellness of a patient.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0034] Hereinafter, various example embodiments of the present
disclosure will be described in detail with reference to the
attached drawings such that the present disclosure can be put into
practice by those skilled in the art. However, the present
disclosure is not limited to the example embodiments, but may be
embodied in various forms.
[0035] Some embodiments will be described in the context of
computer-executable instructions, such as program modules, being
executed by hardware devices, such as embedded processors,
microcontrollers, and computer workstations. Program modules may
include routines, programs, objects, components, data structures,
etc. that perform particular tasks or implement particular data
types. Computer-executable instructions, associated data
structures, and program modules represent examples of program code
for executing steps of the methods disclosed herein. The particular
sequence of executable instructions or arrangement of associated
data structures represents examples of corresponding acts for
implementing the functions described in such steps. A person of
skill in the art would understand that other structures,
arrangements, and executable instructions could be used with the
present disclosure without departing from the spirit thereof.
[0036] FIG. 1 illustrates an embodiment of a physiological
measurement system 100 having a monitor 101 and a sensor assembly
101. The physiological measurement system 100 allows the monitoring
of a person, including a patient. In particular, the multiple
wavelength sensor assembly 101 allows the measurement of blood
constituents and related parameters, including oxygen saturation,
COHb, MetHb and pulse rate.
[0037] In an embodiment, the sensor assembly 101 is configured to
plug into a monitor sensor port 103. Monitor keys 105 provide
control over operating modes and alarms, to name a few. A display
107 provides readouts of measured parameters, such as oxygen
saturation, pulse rate, COHb and MetHb to name a few.
[0038] FIG. 2A illustrates a multiple wavelength sensor assembly
201 having a sensor 203 adapted to attach to a tissue site, a
sensor cable 205 and a monitor connector 201. In an embodiment, the
sensor 203 is incorporated into a reusable finger clip adapted to
removably attach to, and transmit light through, a fingertip. The
sensor cable 205 and monitor connector 201 are integral to the
sensor 203, as shown. In alternative embodiments, the sensor 203
can be configured separately from the cable 205 and connector 201,
although such communication can advantageously be wireless, over
public or private networks or computing systems or devices, through
intermediate medical or other devices, combinations of the same, or
the like.
[0039] FIGS. 2B-C illustrate alternative sensor embodiments,
including a sensor 211 (FIG. 2B) partially disposable and partially
reusable (resposable) and utilizing an adhesive attachment
mechanism. Also shown is a sensor 213 being disposable and
utilizing an adhesive attachment mechanism. In other embodiments, a
sensor can be configured to attach to various tissue sites other
than a finger, such as a foot or an ear. Also a sensor can be
configured as a reflectance or transflectance device that attaches
to a forehead or other tissue surface. The artisan will recognize
from the disclosure herein that the sensor can include mechanical
structures, adhesive or other tape structures, Velcro wraps or
combination structures specialized for the type of patient, type of
monitoring, type of monitor, or the like.
[0040] Certain physiological parameters and certain changes in
physiological parameters may serve as indicators of an adverse
condition affecting a patient. For example, an increase in blood
methemoglobin (MetHb) concentration may be useful as a marker of
the onset of sepsis or septic shock. As another example,
measurements of high blood carboxyhemoglobin (COHb) concentration
may indicate exposure to carbon monoxide (CO). Other physiological
and related parameters to which techniques of the present
disclosure may be applicable include respiration rate, respiration
volume, oxygen saturation, pulse rate, ECG, blood glucose, blood
pressure, temperature, perfusion index, exhaled carbon dioxide
waveform, end tidal carbon dioxide, various signal quality
indicators, data confidence indicators and trend data, among
others.
[0041] A sensor measuring a physiological parameter (e.g., a
physiological parameter measurement device) of a patient may, under
certain circumstances, detect a change in the magnitude of a
detected signal that does not correspond to a change in the value
of the physiological parameter. Such changes in a detected signal
may occur, for example, when the sensor is moved to a different
measurement site. Sometimes, a sensor may be temporarily removed
from a patient, and medical reasons may compel movement of the
sensor to a different location. For example, a multiple wavelength
sensor may need to be moved to a different finger of a patient
about every 12 hours in order to maintain the sensor's measurement
effectiveness and/or to avoid injury to the patient. When the
measurement site of a multiple wavelength sensor is switched to a
different location, the magnitudes of some of the signals detected
by the sensor may change, even though no significant change in the
patient's physiological parameters has occurred during the brief
sensor relocation period. Signal normalization techniques described
in the present disclosure may reduce changes in physiological
parameters reported by a physiological parameter system that are
unrelated to actual physiological parameter variation.
[0042] In some cases, the magnitude of a sensor measurement may be
a less effective indicator of an adverse condition than a change in
the magnitude of a sensor measurement. In such cases, a sensor may
not need to be calibrated to report the absolute magnitude of a
physiological parameter when changes in the magnitude of the
parameter are more significant for purposes of condition detection.
In other cases, the absolute magnitude of a physiological parameter
is valuable, and a sensor signal must be analyzed and/or
recalibrated to compensate for changes in the magnitude of the
signal detected that do not correspond to changes in the value of
the physiological parameter being measured. Signal normalization
techniques may improve a physiological parameter system's reporting
effectiveness for both types of parameters.
[0043] FIG. 3A illustrates an example chart 300 of the value of a
physiological parameter, such as, for example, MetHb, as measured
by a sensor during a time when the sensor is moved from one
measurement site to another. Chart 300 shows the magnitude of a
signal measured by a sensor as a function of time before any
analysis or manipulation of the signal occurs. A first axis 302 of
chart 300 represents time, and a second axis 304 represents the
magnitude of a signal, corresponding to a physiological parameter,
detected at a point in time. The physiological parameter
corresponding to the signal shown by way of example in FIG. 3A is
blood MetHb concentration.
[0044] Curve 306 represents the magnitude of the signal detected by
a sensor during a period when the sensor was at a first measurement
site. The signal represented by curve 306 roughly oscillates about
a nearly constant mean value of the signal. However, the signal may
also follow any continuous increasing or decreasing trend and may
also be nonoscillatory or contain a complex pattern of
variation.
[0045] At time T1 along axis 302, the sensor is removed from the
first measurement site. Curve 308 represents the magnitude of the
signal detected by the sensor while it is disconnected from the
patient, for example, while a care provider switches the sensor to
a new measurement site. In chart 300, the magnitude of the signal
is about zero, but the sensor may continue to detect a signal of
some nature (e.g., random noise, background interference, etc.)
during a period when it is disconnected from a patient.
[0046] At time T2 along axis 302, the sensor is attached to a
second measurement site on the patient. The second measurement site
may be different than the first measurement site; for example, the
second measurement site may be a different finger or a different
position on a finger. Curve 310 represents the magnitude of the
signal detected by the sensor during a period when the sensor is at
the second measurement site. The signal represented by curve 310
roughly oscillates about a nearly constant mean value of the signal
that is higher than the mean value of the portion of the signal
represented by curve 306. The difference between the magnitude of
the signal shortly before time T1 and the magnitude of the signal
shortly after time T2 is a shift in the magnitude of the signal
that is related to the change in the measurement site. However, the
shift in the signal may not correspond to an actual change in the
value of a physiological parameter of the patient. In some cases,
it may be safe to assume that the approximate value of a
physiological parameter shortly before time T1 and shortly after
time T2 is the same. In the absence of signal normalization, the
signal shift may trigger a false alarm or cause a physiological
parameter system to incorrectly report a change in a parameter. In
the embodiment shown in FIG. 3A, reporting the non-normalized
signal may trigger an alarm for sepsis or septic shock at time T2
due to an apparent increase in blood MetHb concentration.
[0047] FIG. 3B illustrates a chart 350 of a physiological parameter
reported by a measurement system employing signal normalization
techniques. In the situation corresponding to chart 350, it is
assumed that the approximate value of the physiological parameter
shortly before time T1 is the same as the approximate value of the
physiological parameter shortly after time T2. A first axis 352 of
chart 350 represents time, and a second axis 354 represents the
value of a physiological parameter reported by a physiological
parameter system at a point in time. The physiological parameter
shown by way of example in FIG. 3B is blood MetHb
concentration.
[0048] In chart 350, curve 356 represents the value of the
physiological parameter reported while the sensor is at the first
measurement site. Curve 358 represents the value of the
physiological parameter reported while the sensor is not connected
to the patient. In alternative embodiments, a physiological
parameter system may not report a parameter or may shut off the
sensor when the system detects that the sensor is not at a
measurement site. Curve 360 represents the value of the
physiological parameter reported while the sensor is at the second
measurement site. The physiological parameter data in chart 350 is
normalized because the value of the physiological parameter
reported just before T1 is adjusted to match the value of the
physiological parameter just after T2. Various methods of matching
may exist, including adjusting the values before and after the
measurement site change to be approximately equal, using data
points before T1 to generate a trend line and fixing the data point
at T2 to the trend line, or any other method known in the art of
projecting or approximating the value of the physiological
parameter at T2 based on data prior to T1.
[0049] In some embodiments, sensor measurements that are received
after time T2, as shown in curve 310 of chart 300 (FIG. 3A), may be
normalized by adding an offset to the magnitudes of the
measurements. The offset may be calculated by subtracting the
magnitude of the non-normalized sensor measurement at time T2 from
the magnitude of the normalized sensor measurement at T2. The
offset may be a negative number. Similar methods of normalizing
data points involving, for example, subtraction of an offset and
other known methods may also be used. One result of signal
normalization is that, given a relatively constant physiological
parameter over time, the mean value of curve 360 will more closely
approximate the mean value of curve 356. Signal normalization may
reduce the incidence of false alarms and reports of changes in
physiological parameters that have not in fact changed.
[0050] FIG. 3C illustrates a further example of normalizing a
signal with erratic noise, such as, for example, motion induced
noise. As illustrated, a physiological parameter signal 370, such
as a signal indicative of MetHb, is illustrated. The physiological
parameter signal 370 includes various inconsistencies, such as, for
example, erratic noises 371, probe off conditions 373, and cite
change conditions 375. In order to deal with these inconsistencies,
processing is used to determine a normalization 377 or trend of the
signal. The normalization 377 uses various methods in order to
determine a relatively stable physiological parameter reading
377.
[0051] FIG. 3D illustrates a flow chart of a normalization
procedure 380. For ease in discussion, FIGS. 3D and 3E will be
discussed with respect to a MetHb reading, however, it should be
understood that any physiological parameter can be used with the
present disclosure. The normalization procedure begins with the
data signal 381. As show, the normalization feature 380 includes
Met calculator 382; smoother 384, Met signal extractor 385; signal
quality 387 and distortion 388. In an embodiment, a data signal 381
responsive to an intensity signal is input into the Met calculator
382, and a current value 383 of Met is calculated. The current
value 383 of Met, which in an embodiment is subject to noise,
distortion, and site movements in the data signal 381, is input
into the smoother 384, which reduces an error between the current
value 383 of Met and actual MetHb conditions. For example, the
smoother 384 may advantageously determine a Met trend, and
depending upon an indication of some or all of an amount of
distortion, noise, signal quality, and/or waveform quality in the
data signal 383, substitute or combine the MetHb trend for or with
the current value 383 to generate an output MetHb measurement.
[0052] In an embodiment, the distortion signal 388 may comprise a
Boolean value indicating whether the data signal 383 includes, for
example, motion-induced noise. Although an artisan will recognize
from the disclosure herein a number of methodologies for deriving
the distortion signal 388, derivation of a Boolean distortion
signal is disclosed in U.S. Pat. No. 6,606,511, incorporated herein
by reference. Alternatively, or in addition to, the signal quality
signal 387 may comprise a Boolean value indicating whether the data
signal 383 meets various waveform criteria Although an artisan will
recognize from the disclosure herein a number of methodologies for
deriving the signal quality signal 387, derivation of a Boolean
distortion signal is disclosed in the '511 patent. Alternatively,
or in addition to, a feature extractor 385 may advantageously
produce waveform quality outputs 386, indicative of waveform
quality or waveform shape. Although an artisan will recognize from
the disclosure herein a number of methodologies for deriving the
waveform quality signal 386, derivation thereof is disclosed in
U.S. Pat. No. 6,334,065, also incorporated herein by reference.
[0053] Thus, the smoother 384 accepts one or more or different
indicators of the quality of the data signal 381, and determines
how to smooth or normalize the output to reduce errors between data
trends and actual MetHb conditions. In an embodiment, the smoothing
may advantageously comprise statistical weighting, other
statistical combinations, or simply passing the MetHb measurement
383 through to the output, depending upon one or more of the
quality signals 386, 387, 388, or logical combinations thereof.
[0054] Upon the output of the normalized MetHb measurement, a
monitor may advantageously audibly and/or visually presents the
measurement to a caregiver, and when the measurement meets certain
defined thresholds or behaviors, the monitor may advantageously
audibly and/or visually alert the caregiver. In other embodiments,
the monitor may communicate with other computing devices to alert
the caregiver, may compare longer term trend data before alarming,
or the like.
[0055] FIG. 3E illustrates a simplified block diagram of an
embodiment of a MetHb determination system 390 using multiple Met
calculation techniques. As shown, data 391 is input into the
system. The data 391 is then routed to at least two different Met
calculators 392, 393. In an embodiment, more than two different
types of calculation techniques can be used. The at least two Met
calculators 392, 393 output Met indications for input into the Met
selector 395. The Met selector 395 determines a Met value to
output. The Met selector chooses the output based on which Met
calculator works best for a given condition of the signal or based
on which Met calculation fits the trend of Met readings. Other
methods of selecting the best Met value can also be made as would
be understood by a person of skill in the art from the present
disclosure.
[0056] FIG. 4 is a block diagram of a physiological parameter
system having signal normalization capability. A physiological
parameter system may include a sensor signal analysis subsystem 400
that implements signal normalization techniques. Signal analysis
subsystem 400 receives a signal 402 from a physiological parameter
measurement device output. Signal 402 may be, for example, an
electrical signal produced by an optical transducer within a pulse
oximeter or a capnometer.
[0057] In the embodiment shown in FIG. 4, signal 402 is
communicated to a sensor event module 404. Sensor event module 404
includes program code for detecting events that occur based on a
pattern recognized in signal 402. Detected events may include a
change in measurement site, movement of the sensor, interference in
the signal, etc. For example, sensor event module 404 may determine
that a measurement site of the sensor has been exchanged if a
normal physiological parameter pattern ceases for a short period of
time and then resumes. Alternatively, sensor event module 404 may
detect a measurement site switch when signal 402 is interrupted by
an interval of random noise and/or a relatively large discontinuity
in the signal. Alternatively, an operator can indicate an event,
such as a location change, by, for example, pressing a
predetermined function button. As another example, sensor event
module 404 may determine that signal normalization may not be
appropriate when a sensor has been disconnected from a measurement
site for a sufficiently long period of time (e.g., when an
assumption that a signal trend will continue is no longer sound).
Sensor event module 404 may communicate signal 402 and/or event
information to a sensor memory 406 to store sensor signal pattern
data for later use. Sensor event module 404 may also communicate
signal 402 and event information to signal normalization module
408.
[0058] Sensor memory 406 may retain a certain number of signal 402
samples or may retain signal 402 samples for a certain period.
Retained samples may be used by program code in signal
normalization module 408 and/or sensor event module 404. Samples
from signal 402 may be stored in a queue data structure, for
example. In some embodiments, sensor event module 404 may instruct
sensory memory 406 to cease storing new samples when it determines
that the sensor is not connected to a measurement site so that
signal data for potential future signal normalization may be
retained. Signal memory 406 may also retain signal offset or
calibration data.
[0059] Signal normalization module 408 comprises program code for
converting a signal 402 from a sensor output into a normalized
measure of a physiological parameter. Program code in module 408
may, for example, add or subtract a value from signal 402 in order
to eliminate shifts in the magnitude of signal 402 that are not
related to variation in a patient's physiological parameters.
Signal normalization module 408 may determine an offset that
counterbalances a shift in signal 402 that results from a change in
sensor measurement site. Module 408 may include program code for
calculating a trend line from data stored in sensor memory 406. A
trend line may be used to determine an appropriate value for a
patient parameter when measurement resumes after an interruption in
signal 402. Module 408 may also employ pattern recognition or
signal transforms to help it determine how signal 402 should be
normalized. Sensor event module 404 may trigger signal
normalization module 408 to reset its signal normalization when a
certain signal events are detected. In some embodiments, sensor
event module 404 may communicate to signal normalization module 408
the retained signal data from sensor memory 406 it should use to
calculate a new offset. Signal normalization module 408 passes a
normalized signal 450 out of signal normalization subsystem
400.
[0060] Normalized signal 450 may then be passed to other components
of a physiological parameter system for further analysis and/or
display. For example, normalized signal 450 may be communicated to
a comparator 454 that compares signal 450 to one or more parameter
limits 452. In some embodiments, comparator 454 may generate an
alarm signal 456 if normalized signal 450 falls outside of
parameter limits 452.
[0061] FIG. 5 illustrates an embodiment of a method for normalizing
a signal acquired by a sensor when the measurement site of the
sensor is changed. At step 502, sensor memory 406 (FIG. 4)
maintains recent physiological parameter measurements received from
sensor output 402. Sensor signal data may be passed directly to
sensor memory 406 for storage, or sensor event module 404, for
example, may select which signal samples will be retained and pass
them to sensor memory 406. Retained signal sample data may include
the magnitude of the signal as well as an indicator of the time
that the sample was taken and/or the order in which the sample was
received. Alternatively, sensor memory 406 may simply maintain
signal data in chronological order in a queue, purging old sample
data as new sample data is received. Data may be retained only for
a certain time interval, such several seconds, a fraction of a
minute, a minute, two minutes, or longer. The interval of retention
may vary depending on the physiological parameter associated with
signal 402. This step may continue until sensor event module 404
detects a sensor measurement site change.
[0062] In step 504 of FIG. 5, sensor event module 404 detects a
change in the sensor measurement site. In some embodiments, sensor
event module 404 may detect the change in measurement site by one
of the methods described with respect to the description of program
code within sensor event module 404 above. Alternatively, a user of
a physiological parameter system may indicate that a change in
sensor measurement site has occurred by means of a hardware or
software interface. For example, the sensor may include a hardware
switch that activates when the measurement site is changed. The
system may also include a manual switch or button that a user can
activate to cause sensor event module 404 to register a change in
the sensor measurement site. When sensor event module 404
determines that sampling at the new measurement site has begun, the
method proceeds to step 506.
[0063] At step 506, signal normalization module 408 compares the
magnitude of the signal sampled at the new measurement site with
the magnitude of the retained signal that was obtained at the old
measurement site. Signal normalization module 408 may use pattern
recognition or signal transform techniques to attempt to compare an
oscillatory signal at similar points in its cycle to obtain a more
accurate comparison. In some embodiments, module 408 uses the
comparison to calculate an offset that adjusts the signal at the
time that measurement at the new measurement site begins to conform
to a trend line fitted to signal data acquired from the old
measurement site. Retained signal data from the old measurement
site may be retrieved from sensor memory 406 and analyzed for the
purpose of calibrating the sensor signal at the new measurement
site. After the initial physiological parameter value is projected
when the sensor begins sampling at the new measurement site, the
method proceeds to step 508.
[0064] In step 508, signal normalization module 408 adjusts the
magnitude of the signal measured at the new measurement site in
order to output a normalized signal 450. In some embodiments,
adjusting the magnitude of the signal measured comprises modifying
the magnitude of a signal measure measurement by adding or
subtracting an offset. For example, the offset may be calculated by
subtracting the magnitude of the signal sampled just after the
sensor begins measurements at the new measurement site from the
magnitude of the signal sampled just before the sensor was removed
from the old measurement site. Alternatively, the offset may be
defined as the difference between (1) a projected value of the
magnitude of the signal just after the sensor begins measurements
at the new measurement site, the projection based on measurements
at the old measurement site, and (2) the actual measured value of
the magnitude of the signal just after the sensor begins
measurements at the new measurement site. Any other known means for
calculating an offset may also be used. Signal normalization module
408 continues to add or subtract the calculated offset until
another normalization step is required. At the conclusion of the
method shown in FIG. 5, the steps shown may be repeated as many
times as changes in the measurement site of the sensor may
require.
[0065] Various embodiments of signal normalization techniques have
been shown and described. Some alternative embodiments and
combinations of embodiments disclosed herein have already been
mentioned. Additional embodiments comprise various other
combinations or alterations of the embodiments described.
[0066] FIG. 6 illustrates a physiological parameter system 600,
which may comprise an expert system, a neural-network or a logic
circuit, for example. The physiological parameter system 600 has as
inputs 601 from one or more parameters from one or more
physiological measurement devices, such as a pulse oximeter 610
and/or a capnometer 620. Pulse oximeter parameters may include
oxygen saturation (SpO.sub.2), perfusion index (PI), pulse rate
(PR), various signal quality and/or data confidence indicators (Qn)
and trend data, to name a few. Capnography parameter inputs may
include, for example, an exhaled carbon dioxide waveform, end tidal
carbon dioxide (ETCO.sub.2) and respiration rate (RR). Signal
quality and data confidence indicators are described in U.S. Pat.
No. 6,108,090 cited above. The physiological parameter system 600
may also have parameter limits 606, which may be user inputs,
default conditions or otherwise predetermined thresholds within the
system 600.
[0067] The inputs 601 are processed in combination to generate one
or more outputs 602 comprising alarms, diagnostics and controls.
Alarms may be used to alert medical personnel to a deteriorating
condition in a patient under their care. Diagnostics may be used to
assist medical personnel in determining a patient condition.
Controls may be used to affect the operation of a medical-related
device. Other measurement parameters 630 that can be input to the
monitor may include or relate to one or more of ECG, blood glucose,
blood pressure (BP), temperature (T), HbCO, MetHb, respiration rate
and respiration volume, to name a few.
[0068] FIG. 6A illustrates an embodiment of a physiological
parameter system 600 similar to the system in FIG. 6. The
physiological parameter system 600 has as inputs 601 from one or
more parameters from one or more physiological measurement devices,
such as, for example a pulse oximeter 610, an acoustic respiratory
monitor 640, an ECG monitor 650, an invasive or non-invasive blood
pressure monitor 650, a thermometer, or any other invasive or
noninvase physiological monitoring devices or the like.
[0069] FIG. 7 illustrates one embodiment of a physiological
parameter system 700 combining pulse oximetry parameter inputs 710
and capnography parameter inputs 720 so as to generate alarm
outputs 702. Parameter limits 705 may be user inputs, default
conditions or otherwise predetermined alarm thresholds for these
parameters 710, 720. The alarms 702 are grouped as pulse oximetry
related 730, capnography related 740 and a combination 750. For
example, a pulse oximetry alarm 730 may be related to percent
oxygen saturation and trigger when oxygen saturation falls below a
predetermined percentage limit. A capnography alarm 740 may be
related to ETCO.sub.2 and trigger when ETCO.sub.2 falls below or
rises above a predetermined mm Hg pressure limit. A combination
alarm 750 may indicate a particular medical condition related to
both pulse oximetry and capnography or may indicate a malfunction
in either instrument.
[0070] FIG. 8 illustrates a SpO.sub.2 alarm embodiment 800 that is
responsive to ETCO.sub.2. In particular, a SpO.sub.2 alarm 805 may
be triggered sooner and may indicate a high priority if ETCO.sub.2
803 is falling. That is, if ETCO.sub.2 803 is trending down above a
certain rate, the SpO.sub.2 alarm 805 is triggered at a higher
percentage oxygen saturation threshold and alerts a caregiver to
the possibility of a serious condition, e.g. a pulmonary
embolism.
[0071] As shown in FIG. 8, a slope detector 810 determines the
slope 812 of the ETCO.sub.2 input 803. A slope comparator 820
compares this slope 812 to a predetermined slope limit 804. If the
downward trend of ETCO.sub.2 803 is great enough, a delta value 803
is added 840 to the SpO.sub.2 lower limit 802 to generate a
variable threshold 842. A threshold comparator 850 compares this
variable threshold 842 to the SpO.sub.2 input 801 to generate a
trigger 852 for the SpO.sub.2 alarm 805. The alarm volume,
modulation or tone may be altered to indicate priority, based upon
the slope comparator output 822.
[0072] FIG. 9 illustrates a CO.sub.2 alarm embodiment 900 that is
responsive to SpO.sub.2. In particular, morphology of the input
CO.sub.2 waveform 901 is utilized to trigger an alarm 905, and that
alarm is also responsive to a falling SpO.sub.2 902. That is, if a
pattern in the CO.sub.2 waveform is detected and SpO.sub.2 is
trending down above a certain rate, then an alarm is triggered. For
example, an increasing slope of the CO.sub.2 plateau in combination
with a downward trend of SpO.sub.2 may trigger an alarm and alert a
caregiver to the possibility of an airway obstruction.
[0073] As shown in FIG. 9, a pattern extractor 910 identifies
salient features in the CO.sub.2 waveform and generates a
corresponding feature output 912. A pattern memory 920 stores one
or more sets of predetermined waveform features to detect in the
CO.sub.2 input 901. The pattern memory 920 is accessed to provide a
feature template 922. A feature comparator 930 compares the feature
output 912 with the feature template 922 and generates a match
output 932 indicating that a specific shape or pattern has been
detected in the CO.sub.2 waveform 901. In addition, a slope
detector 940 determines the slope 942 of the SpO.sub.2 input 902. A
slope comparator 950 compares this slope 942 to a predetermined
slope limit 904. If the downward trend of SpO.sub.2 902 is great
enough, a slope exceeded output 952 is generated. If both the match
output 932 and the slope exceeded output 952 are each asserted or
"true," then a logical AND 960 generates a trigger output 96 to the
alarm 970, which generates an alarm output 905.
[0074] FIG. 10 illustrates a combination embodiment 1000 having a
diagnostic output 1005 responsive to both SpO.sub.2 1001 and
CO.sub.2 1003 inputs. A SpO.sub.2 slope detector 100 determines the
slope 102 of the SpO.sub.2 input 1001 and can be made responsive to
a negative slope, a positive slope or a slope absolute value. A
first comparator 1020 compares this slope 102 to a predetermined
SpO.sub.2 slope limit 1002. If the trend of SpO.sub.2 1001 is great
enough, a SpO.sub.2 slope exceeded output 1022 is asserted.
Likewise, an CO.sub.2 slope detector 1030 determines the slope 1032
of the CO.sub.2 input 1003. A second comparator 1040 compares this
slope 1032 to a predetermined CO.sub.2 slope limit 1004. If the
downward trend of CO.sub.2 1001 is great enough, an CO.sub.2 slope
exceeded output 1042 is asserted. If both slope exceeded outputs
1022, 1042 are asserted or "true," a diagnostic output 1005 is
asserted.
[0075] In one embodiment, the slope detectors 610, 1030 are
responsive to a negative trend in the SpO.sub.2 1001 and CO.sub.2
1003 inputs, respectively. Accordingly, the diagnostic output 1005
indicates a potential embolism or cardiac arrest. In another
embodiment, the SpO.sub.2 slope detector 610 is responsive to
negative trends in the SpO.sub.2 1001 input, and the CO.sub.2 slope
detector 1030 is responsive to a positive trend in the CO.sub.2
1003 input. Accordingly, the diagnostic output 1005 indicates a
potential airway obstruction. The diagnostic output 1005 can
trigger an alarm, initiate a display, or signal a nursing station,
to name a few.
[0076] FIGS. 11A-B illustrate a physiological parameter system 1100
utilizing pulse oximetry to control patient controlled analgesia
(PCA). In particular embodiments, a control output 1108 is
responsive to pulse oximetry parameters 1101 only if signal quality
1103 is above a predetermined threshold 1104. In FIG. 11A, the
control output 1108 can be used to lock-out patient controlled
analgesia (PCA) if pulse oximetry parameter limits have been
exceeded. If signal quality is so low that those parameters are
unreliable, however, PCA is advantageously allowed. That is, the
pulse oximeter parameters are not allowed to lock-out PCA if those
parameters are unreliable. By contrast, in FIG. 11B, the control
output 1108 can be used to advantageously lock-out or disable
patient controlled analgesia (PCA) if pulse oximetry parameter
limits have been exceeded or if signal quality is so low that those
parameters are unreliable.
[0077] As shown in FIG. 11A, pulse oximetry parameters 1101 and
corresponding limits 1102 for those parameters are one set of
inputs and a signal quality measure 1103 and a corresponding lower
limit 1104 for signal quality are another set of inputs. The
parameters 1101 and corresponding limits 1102 generate a combined
output 1202 that is asserted if any of the pulse oximetry parameter
limits are exceeded. A comparator 1110 compares the signal quality
1103 input with a lower limit 1104 generating a quality output 1112
that is asserted if the signal quality 1103 drops below that limit
1104. An AND logic 1120 generates a reset 1122 if the combined
output 1202 is asserted and the quality output 1112 is not
asserted. The reset 1122 resets the timer 1130 to zero. A
comparator 1140 compares the timer output 1132 to a predetermined
time limit 1106 and generates a trigger 1142 if the time limit is
exceeded. The trigger 1142 causes the control 1150 to generate the
control output 1108, enabling a patient controlled analgesia (PCA),
for example. In this manner, the PCA is enabled if all monitored
parameters are within set limits and signal quality is above its
lower limit for a predetermined period of time.
[0078] As shown in FIG. 11B, the combined output 1202, quality
output 1112, reset 1122, timer 1130, comparator 1140 and control
1150 are generated as described with respect to FIG. 11A, above. An
OR logic 1121 generates a reset 1122 if either the combined output
1202 or the quality output 1112 is asserted. In this manner, the
PCA is disabled for a predetermined period of time if any of the
monitored parameters are outside of set limits or the signal
quality is below its lower limit.
[0079] FIG. 12 illustrates combined limits 1200 having SpO.sub.2
parameters 1101 and corresponding thresholds 1102 as inputs and
providing a combination output 1202. In particular, if any
parameter 1101 exceeds its corresponding limit 1102, the output of
the corresponding comparator 1210, 1220, 1240 is asserted. An OR
logic 1250 is responsive to any asserted output 1212, 1222, 1242 to
asserted the combined output 1202. For example, the combined output
1202 may be asserted if SpO.sub.21201 falls below a lower limit
1209, pulse rate (PR) 1203 rises above an upper limit 1204 or PR
1203 falls below a lower limit 120.
[0080] A physiological parameter system has been disclosed in
detail in connection with various embodiments. These embodiments
are disclosed by way of examples only and are not to limit the
scope of the claims that follow. One of ordinary skill in the art
will appreciate many variations and modifications. For example, the
control output 1108 (FIG. 11B) can be used to control (titrate)
delivered, inspired oxygen levels to patients based upon pulse
oximetry parameters, unless signal quality is so low that those
parameters are unreliable. One of ordinary skill in the art will
also recognize that the control output 1108 (FIG. 11B) can be used
to control patient delivery of any of various pharmacological
agents and/or medical gases.
[0081] FIG. 13 illustrates an embodiment of a system 1300 that
displays an indicator of the wellness of a patient. Various sensors
1302a-1302n communicate with a parameter analysis module 1306.
Sensors 1302a-1302n may include pulse oximeters and capnometers,
among other physiological parameter measurement devices. Sensor
1302n outputs a signal that may be sampled, normalized, and/or
analyzed by modules that are not shown in system 1300 before being
passed to parameter analysis module 1306. As described above,
normalization of sensor signals before comparison of the signals to
parameter limits 452 (FIG. 4) and/or parameter preferences 1304 may
have certain benefits, such as decreased incidence of false alarms
and/or more effective determination of the wellness of the
patient.
[0082] In the embodiment shown, a user may provide parameter
preferences 1304 to parameter analysis module 1306 through a user
interface. Parameter preferences 1304 may include preferred ranges,
less preferred ranges, least preferred ranges, upper limits, lower
limits, preferred rates of increase or decrease, preferred patterns
or trends, preferred states, or any combination of such preferences
or other standards for evaluating the desirability of various
physiological parameter values and signals. In some cases, a user
of system 1300 may provide custom preferences to override a default
set of physiological parameter preferences 1304 preprogrammed into
system 1300. In some embodiments, parameter analysis module 1306
may include program code for dynamically changing or suggesting
changes to various parameter preferences as a function of certain
physiological parameters or related sensor performance data.
[0083] Parameter analysis module 1306 compares at least some of the
signal data received from sensors 1302a-1302n to parameter
preferences 1304 in order to calculate an indicator of the wellness
of a patient. In some embodiments, the indicator calculated is a
numerical indicator; for example, a number between one and ten,
where a ten corresponds to a patient with a high level of wellness,
and a one corresponds to a patient with a very low level of
wellness as depicted in FIG. 13B. Other ranges, such as one to 100,
-100 to 100, etc., and scales, such as an alphabetic A-F scale or a
color scale, may also be used including the scale depicted in FIG.
13A. Other indicators that may be generated by parameter analysis
module 1306 include graphical indicators of potential trouble
areas, gauges, charts, level meters, and the like may also be used.
Parameter analysis module 1306 communicates the indicator to a
display 1308, which may display the indicator in any suitable
graphical or textual form that is known in the art. For example,
display 1308 may show a number of bars or a level meter, the number
of which may correspond to one of the numerical indicator scales
discussed above.
[0084] FIG. 14 is a flowchart showing an example method of
displaying an indicator of the wellness of a patient. At step 1402,
parameter analysis module 1306 (FIG. 13) receives signal data from
one or more sensors 1302a-1302n. As discussed previously, such
signal data may be normalized or otherwise modified from its raw
form before being passed to parameter analysis module 1306.
Parameter analysis module 1306 may continuously update an indicator
as new data is received and may calculate averages, variances,
and/or other analytical measures of various physiological
parameters over time. In some embodiments, parameter analysis
module 1306 may update the indicator of patient wellness only
periodically, sporadically, or by request rather than continuously,
thus requiring only occasional reception of data from sensors
1302a-1302n.
[0085] In step 1404, parameter analysis module 1306 receives
parameter preferences 1304. Preferences 1304 may by received only
once or sporadically as a user supplies custom preferences.
Preferences 1304 may also be received and/or updated continuously
when, for example, parameter preferences 1304 are functions of
various physiological or sampling parameters.
[0086] At step 1406, parameter analysis module 1306 compares the
data received from sensors 1302a-1302n to parameter preferences
1304. Individual sensor measurements may be compared to parameter
preferences 1304, or parameter analysis module may compare
parameter preferences 1304 to a moving average of sensor
measurements, for example. Comparison of various other known
analytical measures of sensor data is also possible and within the
scope of the present disclosure. The comparison performed by
parameter analysis module 1306 may include magnitude comparisons,
pattern analysis, and/or trend analysis. Historical sensor data may
also be used in the comparison.
[0087] In step 1408 of FIG. 14, parameter analysis module 1306
generates an indicator of the wellness of the patient based on the
comparison performed in step 1406. The indicator may be in any of
the forms discussed previously. For example, module 1306 may
increase a wellness score (e.g., a numerical indicator of wellness)
when physiological parameters fall within preferred ranges or when
sensor signals follow preferred patterns and/or trends. The
indicator may comprise a simple or a more detailed textual and/or
graphical summary of the patient's wellness as interpreted from
parameters measured by sensors 1302a-1302n. In some embodiments,
the indicator may be a scaled number in combination with a textual
description of the patient's wellness score and/or conditions that
may be affecting the score. In addition, particular a particular
condition affecting the patient can also be generated for
communication to a healthcare provider, such as, for example,
sepsis, septic shock, apnea, heart failure, airway obstruction,
carbon monoxide poisoning, low oxygen content, etc.
[0088] After parameter analysis module 1306 generates the wellness
indicator, it sends the indicator to display 1308 at step 1410.
Display 1308 may be integrated with physiological parameter system
1300 or may be a separate display device. The display may also
include auditory sounds, such as for example, beeps, voices, words,
etc., to indicate a particular event or condition occurring.
[0089] Although the foregoing invention has been described in terms
of certain preferred embodiments, other embodiments will be
apparent to those of ordinary skill in the art from the disclosure
herein. Additionally, other combinations, omissions, substitutions
and modifications will be apparent to the skilled artisan in view
of the disclosure herein. It is contemplated that various aspects
and features of the invention described can be practiced
separately, combined together, or substituted for one another, and
that a variety of combination and subcombinations of the features
and aspects can be made and still fall within the scope of the
invention. Furthermore, the systems described above need not
include all of the modules and functions described in the preferred
embodiments. Accordingly, the present invention is not intended to
be limited by the recitation of the preferred embodiments, but is
to be defined by reference to the appended claims.
* * * * *