U.S. patent application number 10/259595 was filed with the patent office on 2003-02-20 for physiological signal monitoring system.
This patent application is currently assigned to VitalSines International, Inc.. Invention is credited to Goodman, Jesse B..
Application Number | 20030036685 10/259595 |
Document ID | / |
Family ID | 24233550 |
Filed Date | 2003-02-20 |
United States Patent
Application |
20030036685 |
Kind Code |
A1 |
Goodman, Jesse B. |
February 20, 2003 |
Physiological signal monitoring system
Abstract
A health monitoring and biofeedback system comprising a
photoplethysmography (PPG) sensor, a processing device, and a Web
site server for determining, displaying and analyzing various
cardiovascular parameters. The PPG sensor is installed within a
manually operated user input device such as a mouse or keyboard,
measures a user's blood volume contour and transmits it to a
processing device such as a personal computer or a personal digital
assistant (PDA). The system determines a plurality of
cardiovascular indices including mean blood pressure, heart rate,
body temperature, respiratory rate, and arterial compliance on the
basis of signal characteristics of the systolic wave pulse and the
systolic reflected wave pulse present within the digital volume
pulse derived from the PPG pulse contour. Signal characteristics of
the systolic reflected wave pulse can be determined through various
pulse analysis techniques including derivative analysis of the
digital volume pulse signal, bandpass filtering or respiratory
matrix frequency extraction techniques. By subtracting the systolic
reflected wave pulse contour from the digital volume pulse contour,
characteristics of the systolic wave pulse can also be identified.
The system also provides for the accurate determination of systolic
and diastolic blood pressure by using a non-invasive blood pressure
monitor to calibrate the relationships between arterial or digital
blood pressure and characteristics of the user's digital volume
pulse contour. In this way, a wide variety of cardiovascular and
respiratory data can be obtained. The system also facilitates the
transmittal of such data to the system web site for further
analysis, storage, and retrieval purposes.
Inventors: |
Goodman, Jesse B.;
(Mississauga, CA) |
Correspondence
Address: |
BERESKIN AND PARR
SCOTIA PLAZA
40 KING STREET WEST-SUITE 4000 BOX 401
TORONTO
ON
M5H 3Y2
CA
|
Assignee: |
VitalSines International,
Inc.
1492 Marshwood Place
Mississauga
CA
L5J 4J6
|
Family ID: |
24233550 |
Appl. No.: |
10/259595 |
Filed: |
September 30, 2002 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
10259595 |
Sep 30, 2002 |
|
|
|
09559424 |
Apr 27, 2000 |
|
|
|
Current U.S.
Class: |
600/300 |
Current CPC
Class: |
G16H 40/67 20180101;
A61B 5/02433 20130101; A61B 5/7239 20130101; G16H 70/20 20180101;
A61B 5/02007 20130101; A61B 5/02241 20130101; A61B 5/6816 20130101;
A61B 5/0002 20130101; A61B 5/021 20130101; A61B 2560/0252 20130101;
A61B 5/02116 20130101; A61B 5/02055 20130101; G16H 40/63 20180101;
G16Z 99/00 20190201; A61B 5/6887 20130101; A61B 5/7207 20130101;
A61B 5/0285 20130101; A61B 5/02416 20130101; A61B 5/1455
20130101 |
Class at
Publication: |
600/300 |
International
Class: |
A61B 005/00 |
Claims
1. A manually operated user input device for simultaneously sensing
a physiological characteristic of a user and for providing input of
data unrelated to the physiological characteristic, said device
comprising: a) a housing having a surface in at least intermittent
contact with a portion of the user's finger; b) at least one PPG
sensor disposed on said surface for sensing the physiological
characteristic of the user; and c) manually operated means for
inputting data to the user input device, said data unrelated to the
physiological characteristic.
2. The user input device of claim 1, wherein said PPG sensor
comprises an LED and a photodiode.
3. The user input device of claim 2, wherein said user input device
comprises two PPG sensors.
4. The user input device of claim 1, wherein said PPG sensor
comprises two LEDs and a photodiode.
5. The user input device of claim 1, 2 or 3, wherein each said PPG
sensor is operating in reflective mode.
6. The user input device of claim 1, 2 or 3, wherein said user
device includes baffle means adapted to house each said LED and
each said photodiode so as to prevent direct coupling of light
between each said LED and each said photodetector.
7. The user input device of claim 1, wherein said user input device
is powered by the universal serial bus of a personal computer.
8. The user input device of claim 1, wherein said user input device
further comprises biasing means for holding said user's finger
against each said PPG sensor with constant and predictable pressure
and for shielding said PPG sensors from ambient light.
9. The user input device of claim 1, wherein a finger cuff bladder
device is used to determine a transfer function relating said blood
volume contour with said pressure pulse contour of the user's
radial artery.
10. The user input device of claim 1, wherein said user device is a
mouse.
11. The user input device of claim 1, wherein said user device is a
track ball.
12. The user input device of claim 1, wherein said user device is a
track pad.
13. The user input device of claim 1, wherein said user device is a
keyboard.
14. The user input device of claim 1, wherein said user device is a
joystick.
15. The user input device of claim 1, wherein said user device is a
personal digital assistant.
Description
[0001] This application is a divisional application of U.S. patent
application Ser. No. 09/559,424 filed on Apr. 27, 2000.
FIELD OF THE INVENTION
[0002] This invention relates to a physiological signal monitoring
system and more particularly to a system which allows a user to
determine various types of physiological information and which
allows a user to electronically access this information over a
communication network.
BACKGROUND OF THE INVENTION
[0003] Various types of instrumentation for monitoring
physiological signals are currently available to consumers and
health professionals. Specifically, consumers have access to
thermometers, weight scales, blood pressure cuffs, blood glucose
monitors, urine testing strips and other similar diagnostic
technology. In the field of cardiovascular physiological testing,
there is currently a wide variety of blood pressure testing
equipment which has been developed to determine arterial blood
pressure related parameters, namely systolic pressure (maximum
blood pressure) and diastolic pressure (minimum blood pressure). It
has also been recognized that other parameters such as mean
(average) blood pressure during a heart cycle, pulse pressure (the
difference between systolic and diastolic pressure) as well as
pulse rate and pulse rhythm are also important in assessing patient
health.
[0004] In an attempt to provide consumers and health professionals
with non-invasive blood pressure measuring equipment for patient
safety and convenience, photoplethysmograph (PPG) sensors have been
utilized within blood pressure testing equipment. PPG sensors are
well-known instruments which use light for determining and
registering variations in a patient's blood volume. They can
instantaneously track arterial blood volume changes during the
cardiac cycle and are used within physiological signs monitoring
devices.
[0005] One such device is disclosed in U.S. Pat. No. 6,047,203 to
Sackner et al. which uses PPG sensors to monitor the physiological
signs of the user to identify when adverse health conditions are
present within the user and to provide the user with appropriate
directions or signals. However, many devices such as this one are
only used to determine whether physiological signals indicate the
presence of an adverse condition for the user and are not directed
to identifying and/or determining accurate estimates of blood
pressure and other cardiovascular values for diagnostic
purposes.
[0006] Since PPG sensors operate non-invasively, efforts have been
made to utilize them to determine estimates of mean, systolic and
diastolic blood pressure. These devices either estimate mean blood
pressure from the mean value of the blood volume pulse, a measure
of pulse wave velocity or changes in the volume pulse contour using
formulae and calibrated constants. However, these devices have not
achieved widespread use due to a lack of accuracy and difficulty of
use.
[0007] Specifically, the difficulties with estimation of mean,
systolic and diastolic blood pressure from the volume pulse contour
can be attributed to variability in the amplitude of the volume
pulse contour due to volume changes unrelated to blood pressure
effects and the nonlinear relationship between volume changes in an
arterial vessel and associated pressure changes.
[0008] Also, there are measurement and instrumentation difficulties
associated with PPG sensors such as the presence of mechanical
alterations in the sensor/skin interface (i.e. vibrations and
differing pressure), ambient light effects, and changes in the
blood volume due to alteration in body position. Without carefully
correcting for changes in the blood volume pulse signal that are
due to factors other than blood pressure and without using
conversion techniques which recognize the nonlinear relationship
between arterial vessel volume and pressure, these methods cannot
accurately predict blood pressure characteristics using PPG
readings alone.
[0009] It has long been recognized that blood volume pulse contours
change with aging and blood pressure. These changes are largely
related to a shift in the occurrence of the aortic reflected wave
within the pulse contour. The reflected wave is a complex pulse
signal generated by reflections of the pulse wave originating at
the heart. The pulse wave travels from the heart along the aorta
with branches to the head and the arms, continues along the aorta
to the trunk and from there to the legs. At about the level of the
kidneys, a significant reflection of the pulse wave originates. The
reflected waves from the arms and the legs are rapidly damped,
travelling with relatively low amplitude back to the trunk. It is
well known that as detected in the upper extremity the reflective
wave originating in the abdominal aorta has an onset later than the
reflected wave from the upper limbs, has significantly greater
amplitude, travels almost without attenuation to the ends of the
upper extremity, and has a significant presence in the volume pulse
contour obtained from a fingertip, ear or other points on the
surface of the body above the aortic origin of the reflecting
wave.
[0010] By accurately characterizing the timing, amplitude and shape
of the abdominal aortic reflected wave, a significant amount of
information about aortic compliance, aortic pulse wave velocity and
the health of the internal organs can be obtained. As discussed in
"Wave Reflection in the Systemic Circulation and its Implications
in Ventricular Function", Michael O'Rourke et al., Journal of
Hypertension 1993, 11 pgs. 327-337, human aortic pulse wave
velocity more than doubles between 17 and 70 years of age. This
phenomenon is a manifestation of arterial stiffening and is
attributable to the fatiguing effects of cyclic stress causing
fracture of load-bearing elastic lamellae in the wall, and
degeneration of arterial wall. When mean blood pressure is
decreased (i.e. using vasoactive drugs), the reflected wave has
been observed to occur later in the pulse wave, whereas when blood
pressure is increased, the reflected wave occurs earlier and moves
into the systolic part of the wave. Readily observed ascending
aortic pressure wave contours associated with ageing and
hypertension can be explained on the basis of early wave
reflection. Also, several authorities have observed a strong
association between poor aortic compliance (i.e. arterial
stiffness) and coronary artery disease and hypertension. For
example, it has been observed that decreased aortic compliance
results in an increase in systolic and a decrease in diastolic
aortic pressure, both of which are deleterious to the heart
("Aortic Compliance in Human Hypertension", Zharorong Liu, et al.,
Hypertension Vol. 14, No. 2, August 1989 pgs. 129-136).
Accordingly, the aortic reflected wave is a powerful source of
information relating to a user's cardiovascular health and relative
risk.
[0011] While there are several techniques for utilizing the timing
of the aortic reflected wave to derive physiologically useful
parameters, the analysis used by most of these techniques does not
accurately identify the onset of the reflected wave in the volume
pulse contour. The subtle changes in the volume pulse signal
associated with aortic reflection effects that follow the systolic
peak are difficult to visualize. It is often extremely difficult to
identify these effects, even with the help of computing means,
without time consuming pattern recognition techniques.
[0012] For example, U.S. Pat. No. 5,265,011 to O'Rourke discloses a
method for determining the systolic and diastolic pressures based
on the specific contours of pressure pulses measured in an upper
body peripheral artery. The method identifies pressure pulse peaks
relating to systolic and diastolic components of the pulse contour
and takes first and third derivatives of the pressure pulses to
determine relevant minimum and maximum points. Specifically, the
onset of the systolic pressure wave is determined by locating a
zero crossing from negative-to-positive on a first derivative curve
and the shoulder of the reflected wave is identified by finding the
second negative-to-positive zero crossing on the third derivative.
However, it is difficult in practise to identify the reflected wave
peak in this fashion as the slope changes of the third derivative
do not consistently indicate the reflected wave peak. In addition,
this method identifies only slope changes in the blood volume pulse
contour. These slope changes are an indirect and imprecise way of
characterizing the timing of the reflected wave component. The high
degree of overlap between the systolic, reflected and dicrotic wave
components obscures the characteristics of the reflected wave.
[0013] Also, many established methods that use PPG techniques and
volume pulse contour analysis and/or pulse wave velocity to derive
blood pressure do not adequately take into account other
complicating effects. For example, the volume pulse contour varies
with changes in blood volume that are unrelated to blood pressure.
Changes in temperature, respiration and body position can all lead
to changes in local blood volume. Movement of a finger relative to
the sensor will also result in unreliable PPG readings. Unless
these factors are controlled, erroneous blood pressure readings
will result.
[0014] Various established methodologies such as the one disclosed
in U.S. Pat. No. 5,876,348 to Sugo et al., derive blood pressure
measures on the assumption that pulse wave velocity and blood
pressure are linearly related. Specifically, in U.S. Pat. No.
5,876,248 mean blood pressure is derived using the formula P=a
PWV+.beta., where P is mean pressure, PWV is pulse wave velocity
and a and .beta. are constants specific to a user. The formula P=a
PWV+.beta. assumes that the relationship between blood pressure and
PWV is linear, which is incorrect. Although the increase in pulse
wide velocity is linear for low pressures, authorities confirm that
the increase is nonlinear with pressure above typical diastolic
pressure ("Measurement of Pulse-Wave Velocity Using a Beat-Sampling
Technique", J. D. Pruett, Annals of Biomedical Engineering, Vol.
16, pgs. 341-347). Further, the relationship between the excursion
of the digital blood volume contour and the arterial pulse pressure
is also nonlinear. Current volume pulse contour analysis techniques
do not take these considerations into account and result in
unreliable determinations.
[0015] Accordingly, there is a need for an improved physiological
characteristic testing device which provides for improved
estimation of various cardiovascular and respiratory indices
through the correct identification of the aortic reflected wave and
arterial blood pressure which facilitates improved communication of
information and biofeedback functionality, uses a minimum of
processing and memory capacity, comprises relatively few parts, and
which is inexpensive to manufacture and operate.
SUMMARY OF THE INVENTION
[0016] It is therefore an object of the present invention, to
provide a physiological signal monitoring system comprising:
[0017] (a) a sensor adapted to come into skin contact with a user
body part, for sensing a physiological characteristic of the user
and for generating electrical signals which correspond to said
physiological characteristic;
[0018] (b) first processing means operatively coupled to said
sensor for receiving and converting said electrical signals into
data, for computing a set of physiological parameters on the basis
of said data, said processing means also being operatively coupled
to a communication network for transmission of said physiological
parameters over said communication network;
[0019] (c) display means coupled to said first processing means for
displaying said physiological parameters; and
[0020] (d) a server coupled to said communications network for
receiving said physiological parameters from said processing means,
for conducting analysis of said first physiological parameters, and
for transmitting information related to said physiological
parameters to said first processing means for display on said
display means.
[0021] In another aspect the invention provides a method of
monitoring the physiological signals of a user comprising the steps
of:
[0022] (a) positioning a sensor in close proximity to a body part
of the user for sensing a physiological characteristic of the user
and for generating electrical signals which correspond to said
physiological characteristic;
[0023] (b) receiving and converting said electrical signals into
data and computing a set of physiological parameters on the basis
of said data;
[0024] (c) displaying said physiological parameters to the
user;
[0025] (d) transmitting said physiological parameters to a server
over a communications network; and
[0026] (e) analyzing said physiological parameters on said server
and transmitting information associated with said physiological
parameters to the user.
[0027] In another aspect the invention provides physiological
signal monitoring system for determining a number of physiological
parameters for a user, said monitoring system comprising:
[0028] (a) a PPG sensor adapted to come into skin contact with the
user for obtaining the blood volume contour of the user;
[0029] (b) filtering means for filtering nonpulsatile and slowly
pulsatile signals from the blood volume contour to obtain a
filtered blood volume pulse signal; and
[0030] (c) processing means for extracting a representation of the
aortic reflected wave contour from the user's filtered blood volume
pulse signal and for determining a plurality of physiological
parameters based on characteristics of said aortic reflected
wave.
[0031] In another aspect the invention provides a method of
determining a number of physiological parameters for a user, said
method comprising the steps of:
[0032] (a) obtaining the blood volume contour of the user using a
first PPG sensor coupled to the user's body, said blood volume
pulse contour containing a plurality of individual blood volume
pulse contour pulses;
[0033] (b) filtering nonpulsatile and slowly pulsatile signals from
the blood volume pulse contour to obtain a filtered blood volume
pulse signal;
[0034] (c) extracting an estimate of the aortic reflected wave
contour from the filtered blood volume pulse signal; and
[0035] (d) determining a plurality of physiological parameters
based on characteristics of said aortic reflected wave.
[0036] The invention also provides a method of determining the
systolic and diastolic blood pressure of a user, in addition to the
steps of determining a number of physiological parameters for a
user described above, comprising the additional steps of:
[0037] (a) performing a series of calibration photolethsympographic
measurements using said first PPG sensor coupled to the skin of the
user over a predetermined calibration period of time;
[0038] (b) performing a series of calibration blood pressure
measurements of the user using a blood pressure monitor coupled to
the user over said predetermined calibration period of time;
[0039] (c) determining at least one transfer function which relates
said calibration blood volume measurements and said calibration
blood pressure measurements;
[0040] (d) calculating a synthesized blood pressure pulse contour,
RADIALsynth, mean arterial blood pressure, MEANABP, and synthesized
pulse pressure, PPsynth, by applying said at least one transfer
function to various indices of said user's blood volume pulse
contour obtained from step (a);
[0041] (e) determining the pulse pressure of the synthesized blood
pressure pulse contour, PP RADIALsynth from said synthesized blood
pressure pulse contour, RADIALsynth;
[0042] (f) calculating the mean amplitude of the synthesized blood
pressure pulse contour, RADIALsynth, namely, MEAN AMP
RADIALsynth;
[0043] (g) calculating the mean fractional amplitude, MEAN AMPFrac,
of said synthesized blood pressure contour, RADIALsynth, according
to the relation: MEAN AMPFrac=MEAN AMP RADIALsynth/PP RADIALsynth;
and
[0044] (h) calculating systolic blood pressure, BPsys, according to
the relation: BPsys=MEANABP+PPsynth (1-MEAN AMPFrac).
[0045] In another aspect, the invention provides a method of
determining the pulse wave velocity of a user, in addition to the
steps of determining a number of physiological parameters for a
user described above, comprising the additional steps of:
[0046] (a) performing steps (a) and (b) using said first PPG sensor
coupled to said user's body at a first location a and a second PPG
sensor coupled to said user's body at a second location b, to
obtain a first filtered blood volume pulse signal at location a and
a second filtered blood volume pulse signal at location b;
[0047] (b) high pass filtering said first and second filtered blood
volume pulse signals;
[0048] (c) performing cross correlation to obtain the time delay
between said first and second filtered blood volume pulse signals
according to the relation: 1 C C ( ) = + .infin. V a ( t ) V b ( t
- ) t
[0049] where CC(.sup..tau.) is the cross correlation which depends
on the time delay between two parameters Va and Vb; Va(.sup..tau.)
and Vb(.sup..tau.) are the corresponding values of the first and
second filtered blood volume pulse signals at the two different
sites on the user's body, a and b, at a time t, and .sup..tau. is
the time delay;
[0050] (d) estimating the travel path for the user; and
[0051] (e) estimating the user's pulse wave velocity on the basis
of said time delay and said travel path.
[0052] In another aspect the invention provides a method for the
extraction of a respiration contour from said blood volume pulse,
in addition to the steps of determining a number of physiological
parameters for a user described above, comprising the additional
steps of:
[0053] (a) calculating an indicia based on said blood volume pulse
contour that correlates with the mean blood pressure of the
user;
[0054] (b) plotting the amplitude values of said indicia over
time;
[0055] (c) interpolating said amplitude values over time to obtain
an interpolated respiratory contour; and
[0056] (d) low pass filtering the interpolated respiratory contour
to obtain the respiration contour.
[0057] In another aspect the invention provides a method for
temperature correcting a user's blood volume pulse contour, in
addition to the steps of determining a number of physiological
parameters for a user described above, comprising the additional
steps of:
[0058] (a) artificially lowering the temperature of the user's
finger prior to step (a) and conducting step (a) as said finger
increases in temperature;
[0059] (b) determining the amplitude of the blood volume pulse
contour and the amplitude of the filtered blood volume pulse signal
at a plurality of sample times, N;
[0060] (c) calculating the changes in amplitude of the blood volume
pulse contour, .DELTA.PPG, and changes in amplitude of the filtered
blood volume pulse signal, .DELTA.DVP, over said plurality of
sample times, N;
[0061] (d) calculating a plurality of constants, Ki for i=N-1
sample times where Ki=.DELTA.PPG/.DELTA.DVP;
[0062] (e) averaging the values of said plurality of constants Ki
to obtain temperature constant K; and
[0063] (f) using said temperature constant K to calibrate readings
of said filtered blood volume pulse signal by using the relation:
.DELTA.PPG=K.DELTA.DVP.
[0064] In another aspect the invention provides a method of
determining a correlate for said plurality of physiological
parameters, in addition to the steps of determining a number of
physiological parameters for a user described above, comprising the
additional steps of:
[0065] (a) twice differentiating said filtered blood volume pulse
signal to produce a second derivative;
[0066] (b) providing a horizontal axis for indicating time with
said second derivative extending above and below said horizontal
axis and located on the horizontal axis at the start of said second
derivative for each pulse; and
[0067] (c) determining the ratio of the height of the second peak
above a first trough of said second derivative relative to the
height of the horizontal axis above the first trough of said second
derivative of said filtered blood volume pulse signal.
[0068] In another aspect the invention provides a manually operated
user input device for simultaneously sensing a physiological
characteristic of a user and for providing input of data unrelated
to the physiological characteristic, said device comprising:
[0069] (a) a housing having a surface in at least intermittent
contact with a portion of the user's finger;
[0070] (b) at least one PPG sensor disposed on said surface for
sensing the physiological characteristic of the user; and
[0071] (c) manually operated means for inputting data to the user
input device, said data unrelated to the physiological
characteristic.
[0072] In another aspect the invention provides a device for
removable attachment to an extremity of the body of a user, said
device comprising:
[0073] (a) a housing having a surface in at least intermittent
contact with a portion of the user's extremity;
[0074] (b) at least one PPG sensor disposed on said surface for
sensing the physiological characteristic of the user; and
[0075] (c) biasing means coupled to said housing for holding said
portion of said extremity against said PPG sensor with constant and
predictable pressure and for shielding said PPG sensors from
ambient light.
[0076] Further objects and advantages of the invention will appear
from the following description, taken together with the
accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0077] In the accompanying drawings:
[0078] FIG. 1 is an illustration of the overall configuration of a
physiological health monitoring system according to the present
invention;
[0079] FIG. 2 is a more detailed illustration of the PPG sensor of
FIG. 1 implemented within a user input device;
[0080] FIG. 3 is a circuit diagram of the PPG sensor and the signal
conditioning module of FIG. 2;
[0081] FIG. 4 is an illustration of an alternative embodiment of
the PPG sensor of FIG. 1;
[0082] FIG. 5 is an illustration of an alternative embodiment of
the user input device and the user's computer as a stand-alone
personal digital assistant (PDA);
[0083] FIG. 6 is an illustration of an alternative embodiment of
the user input device of FIG. 1;
[0084] FIGS. 7A to 7G are illustrations of the variation of shape
of the volume pulse signal contour at different points in the human
body;
[0085] FIG. 8 is a graph of a typical DVP signal contour obtained
from the fingertip of a user by user input device of FIG. 2;
[0086] FIG. 9 is a flowchart showing the general process steps to
obtain cardiovascular and respiratory data which are executed by
the microcontroller of the user input device and the CPU of the
processing device of FIGS. 1 and 2;
[0087] FIG. 10A is a graph showing the DVP signal outputted by the
user input device of FIG. 2;
[0088] FIG. 10B is a graph showing the first derivative of the DVP
signal of FIG. 10A;
[0089] FIG. 10C is a graph showing the second derivative of the DVP
signal of FIG. 10A;
[0090] FIG. 10D is a graph showing the third derivative of the DVP
signal of FIG. 10A;
[0091] FIG. 10E is a graph showing the fourth derivative of the DVP
signal of FIG. 10A;
[0092] FIG. 11A is a graph showing the DVP signal outputted by the
user input device of FIG. 2;
[0093] FIG. 11B is a graph showing the first derivative of the DVP
signal of FIG. 11A;
[0094] FIG. 11C is a graph showing the fourth derivative of the DVP
signal of FIG. 11A;
[0095] FIG. 11D is a graph showing the DVP signal of FIG. 11A after
it has been passed through a 6 to 20 Hz bandpass filter;
[0096] FIG. 12A is a flowchart illustrating a method of the present
invention for extracting the reflected wave contour from the DVP
signal;
[0097] FIG. 12B is a flowchart showing how the individual DVP beats
of the DVP signal are synchronized and normalized;
[0098] FIG. 12C, 12D and 12E are graphs showing three individual
DVP beats;
[0099] FIG. 12F is a spreadsheet table A containing columns of
amplitude data of the DVP beats at different sample times;
[0100] FIG. 12G is a spreadsheet table B containing columns of
interpolated amplitude data of the DVP beats at different
sample-times;
[0101] FIG. 13 is a graph showing various indices on a sample DVP
signal pulse;
[0102] FIG. 14 is a graph showing the derivation of the measure
INDEX.sub.2nd Deriv;
[0103] FIG. 15A is a graph showing the derivation of the mean blood
pressure;
[0104] FIG. 15B is an illustration of the physiological signal
monitoring system of FIG. 1 as used in association with a blood
pressure monitor;
[0105] FIG. 15C is a flow chart illustrating of the calibration
method of the present invention which obtains transfer functions
which relate measures from a user's DVP signal pulse to a pulse
pressure contour, mean arterial blood pressure and radial arterial
pulse pressure;
[0106] FIG. 15D is a flow chart illustrating the blood pressure
determination method of the present invention which derives a
user's systolic, diastolic and pulse pressure from the user's DVP
contour using the physiological signal monitoring system of FIG.
15B;
[0107] FIG. 16A is a flow chart illustrating the steps for
obtaining a respiratory contour for a user using a cardiovascular
parameter obtained from a user's DVP signal;
[0108] FIG. 16B is a graphical representation of a user's DVP
signal;
[0109] FIG. 16C is a graphical representation of the INDEX.sub.2nd
Deriv values obtained for each BEAT of the DVP signal of FIG.
16B;
[0110] FIG. 16D is a graphical representation of a typical
respiratory contour, RESP, obtained from interpolating the
INDEX.sub.2nd Deriv values;
[0111] FIG. 17 is a block diagram of the physiological health
monitoring system of FIG. 1 showing the functionality of the
computation server;
[0112] FIG. 18 is a block diagram of the biometric security system
of the present invention; and
[0113] FIG. 19 is a sample screen capture of the output of the
monitoring system on the display of the processing means of FIG.
1.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0114] Reference is first made to FIG. 1, which shows the overall
configuration of the preferred embodiment of a physiological
monitoring system 10, according to the present invention. System 10
comprises a conventional plethysmography (PPG) sensor 12 coupled to
a processing device 14 which is in data communication with a Web
site server 16 through a communication network 18 (i.e. the
Internet).
[0115] PPGs are well-known instruments which use light for
determining and registering variations in a patient's blood volume.
They can instantaneously track arterial blood volume changes during
the cardiac cycle. PPG sensor 12 is installed within a computer
mouse or some other computer peripheral (e.g. keyboard, touchpad,
joystick) commonly associated with a computer processing device 14.
It should be understood that it would be also possible to implement
the invention by incorporating PPG sensor 12 within the casing of a
personal digital assistant (PDA) or within some other type of stand
alone data processing and transmitting device (e.g. a watch) or
simply as a stand alone sensor device.
[0116] Processing device 14 is preferably a conventional personal
computer having a central processing unit (CPU) 5, display 7,
keyboard 9 and printer 11. Processing device 14 also preferably has
a standard Universal Serial Bus (USB), sufficient memory and
processing power to run the application programs associated with
system 10, and a data transmission controller for sending and
receiving data over data transmission cable 13, all built
integrally with processing device 14. An executable program is
installed within the permanent memory of processing device 14 to
instruct the user through interactive menus to utilize the PPG
sensor 12 such that proper PPG signals can be obtained from the
user and to provide the user with his/her own generated
physiological information through graphical means. It should be
understood that such an executable program could also be available
for downloading online from Web site server 16. The executable
program has the functionality to allow a user to observe his/her
own physiological signals in real time such that biofeedback is
facilitated. Also, it is contemplated that processing device 14
could be used to store a user's physiological signals for later
retrieval, comparative and display purposes. Commercially available
signal measurement and analysis display software such as
LabVIEW.TM. (available from National Instruments of Austin, Tex.)
is utilized to perform the necessary data analysis as well as
display the results of the calculations in easy to understand
format. It should be understood that processing device 14 could
just as easily be a PDA, as discussed above.
[0117] Web site server 16 is a conventional server having
sufficient memory and processing speed to handle the input, storage
and manipulation of large volumes of data being simultaneously
transmitted from a plurality of processing devices 14. Web site
server 16 also must also be capable of transmitting additional
relevant data back to user's computer 14 over communication network
18 for display on a user's processing device 14. Web site server 16
also provides encrypted and password protected secure storage of a
user's physiological signals along with any other health
documentation that the user may desire to store at the Web site.
Web site server 16 could also allow for the storage and restricted
access to a plurality of user's physiological signals (submitted on
an anonymous basis) and associated health documentation for
anonymous medical research purposes.
[0118] Referring now to FIGS. 2 and 3, PPG sensor 12 is shown
installed within a user input device 20 which is coupled to
processing device 14 through data transmission cable 13. In
addition to PPG sensor 12, user input device 20 comprises a
thermistor 23 positioned in close proximity to PPG sensor 12, a
signal conditioner module 24 to condition the raw PPG signal, and a
microcontroller 26 to control the operation of user input device
20.
[0119] PPG sensor 12 has a relatively small footprint (e.g. few
square centimeters) and is implemented using a red LED.sub.1 and an
infrared LED.sub.2, each associated with a photodiode PD.sub.1 and
PD.sub.2 (FIG. 3) in a known configuration for reflective mode
operation (i.e. light is transmitted into a body part and the
amount of light reflected back is detected). The emitted
monochromatic light emitted from LED.sub.1 and LED.sub.2 travels
through a user's finger along a light path which passes through
blood in a plurality of arteries as well as background tissue. As
the monochromatic light travels along its light path it is
partially absorbed by the background tissue and the blood. A
portion of the monochromatic light is not absorbed and is reflected
back to the appropriate photodiode PD.sub.1 or PD.sub.2. As is
conventionally known, reflective mode PPG uses the reflected light
from a site to estimate absorption of light and to generate a raw
blood volume pulse contour signal. The detector is positioned on
the same side as the radiating LED in order to detect the reflected
light.
[0120] Also, as shown in FIG. 2, PPG sensor 12 utilizes cylindrical
baffles 21 to house LED.sub.1 and LED.sub.2 and photodiodes
PD.sub.1 and PD.sub.2 to prevent direct coupling of light from the
LED's to the photodiodes. When a user's finger is placed over the
top openings of baffles 21, light will be only provided to the
finger and spillover light will be appreciably reduced. Well known
techniques to accomplish motion artifact reduction such as that
discussed in PCT Patent Application No. 99/32030 to BTG
International Limitedcould be utilized to further reduce the amount
of motion artifact related distortion of the PPG signal.
[0121] It should be understood that PPG sensor 12 could also be
adapted to operate in transmission mode (i.e. where light is
transmitted through a body part and the amount of light transmitted
through is detected) by making the appropriate changes to the way
PPG sensor 12 is attached a user's finger.
[0122] The particular user input device 20 shown is formed out of a
rigid plastic material and operates as a conventional computer
mouse as well as a diagnostic input tool for detecting a blood
volume contour from a user's finger. Thus, user input device 20
independently receives and sends to processing device 14, data
input from the user which is unrelated to the blood volume contour.
User input device 20 has a depression 22 formed within its housing
that is shaped to receive a user's thumb (a right handed model is
shown) and an elastic restraint 28 is secured on either side of
depression 22.
[0123] PPG sensor 12 is installed within the housing in depression
22 such that PPG sensor 12 is positioned underneath the part of
depression 22 that corresponds to a user's distal thumb and so that
a user's thumb when positioned within depression 22 would be
completely covered by an elastic restraint 28. It has been
determined that this is an optimal configuration, since the
transmitted light can penetrate adequately into the skin at a
user's fingertip and due to the fact that elastic restraint 28
shields PPG sensor 12 from ambient light. For convenient operation
within user input device 20, the LED and photodiode pairs are
installed within depression 22 approximately one centimeter apart
from each other.
[0124] It is known that the movement of the finger relative to the
sensor element will corrupt data from the sensor. It is necessary
to restrict finger motion in a way that decreases motion while at
the same time does not impeded arterial flow or prevent venous
flow. Elastic restraint 28 decreases movement of the thumb relative
to the sensor and applies a constant and predictable biasing force
that presses the thumb against PPG sensor 12. The use of elastic
restraint 28 which is adapted to gently but securely bias the
finger against the PPG sensor 12 helps to recreate the same
pressure of a user's finger against PPG sensor 12 and to ensure
that the change in the PPG signal pulse obtained from the finger
due to blood pressure changes will be consistent from one use of
system 10 to another. The time multiplexed output current from the
photodiodes PD.sub.1 and PD.sub.2 and the thermistor 22 (FIG. 3) is
then applied to signal conditioner module 24.
[0125] FIG. 3 shows the circuity of signal conditioner module 24.
Signal conditioner module 24 uses two identical conditioning
circuits to condition the current output of photodiodes PD.sub.1
and PD.sub.2 independently. The operation of the circuit which
conditions the current signal of photodiode PD.sub.1 will be
discussed, but it should be understood that the circuit which
conditions photodiode PD.sub.2 operates identically. The components
of the circuit which conditions the current signal output of
photodiode PD.sub.2 are identified with the same reference numbers
as for the circuit for photodiode PD.sub.1, but with the part
numbers primed.
[0126] Each circuit includes operational quad amplifiers U1A and
U2A fabricated on a single IC (e.g. Texas Instruments brand TLC274
Precision Quad Operational Amplifier) as well as capacitors
C.sub.1, C.sub.5, C.sub.6, and C.sub.8, resistors R.sub.11,
R.sub.12, R.sub.13, R.sub.14, R.sub.15, R.sub.16, and R.sub.18 and
variable resistor VR.sub.17.
[0127] The operational amplifier U.sub.1A, PD.sub.1, C.sub.5 and
R.sub.12 form a transimpedance photodetector circuit. The raw PPG
photo current signal generated by PD.sub.1 is converted to a
voltage signal through resistor R.sub.12. The combination of
capacitor C.sub.5 and resistor R.sub.12 provides low pass filtering
for the raw PPG voltage signal generated at the output of
operational amplifier U.sub.1A (at node A in FIG. 3). This
configuration eliminates high frequency noise and high frequency
spurious signals which may be present at the input to U.sub.1A.
[0128] The output of operational amplifier U.sub.1A follows two
signal paths. The first path connects the raw PPG voltage signal to
a unity gain buffer circuit comprised of operational amplifier
U.sub.3A and resistor R.sub.18. The raw PPG voltage signal can be
simultaneously monitored or utilized by system 10 (at point A in
FIG. 3) as will be discussed, while the raw PPG voltage signal is
further processed by the second path in the circuit to produce a
conditioned PPG voltage signal (at point B in FIG. 3).
[0129] The second path in the circuit (FIG. 3) connects the raw PPG
voltage signal to a series of signal conditioning stages. The first
conditioning stage is a `Sallen and Key` high pass filter. This
filter is comprised of capacitors C.sub.6 and C.sub.1, resistors
R.sub.13 and R.sub.14 and operational amplifier U.sub.4A. The
values of capacitors C.sub.6 and C.sub.1 and resistors R.sub.13 and
R.sub.14 are chosen to provide the high pass filter with a corner
frequency of approximately 0.1 Hertz. The purpose of this filtering
stage is to suppress low frequency noise within the PPG voltage
signal.
[0130] Following this filtering process, the PPG voltage signal is
applied to a combined amplifier and low pass filter stage comprised
of resistors R.sub.15, R.sub.11 and R.sub.16, variable resistor
VAR.sub.17, capacitor C.sub.8 and operational amplifier U.sub.2A.
The gain of the amplifier is set by adjusting variable resistor
VAR.sub.17. The values of resistors R.sub.16, R.sub.17 and
capacitor C.sub.8 determine the corner frequency which is typically
30 Hertz. The conditioned PPG voltage signal generated by this
stage (at point B) is provided to the processing device 14. In this
way signal conditioner module 24 improves the signal to noise ratio
of the PPG signal prior to digitization.
[0131] In order to power both the high pass filter and combined
amplifier and low pass filter stage discussed above from the
Universal Serial Bus of processing device 14, it is necessary to
provide these circuits with a false ground as is conventionally
known. The false ground circuit is comprised of variable resistor
VAR.sub.2, resistors R.sub.22, R.sub.21, R.sub.23, capacitors
C.sub.9, C.sub.10 and operational amplifier U.sub.1B. The false
ground circuit is a low impedance circuit which can respond quickly
to changes in input current. By adjusting the variable resistor
VAR.sub.2, the ground reference can be shifted between zero and 5
volts DC. By shifting the ground reference level, the conditioned
PPG voltage signal can be DC shifted accordingly.
[0132] Accordingly, the PPG voltage signal from photodiodes
PD.sub.1 and PD.sub.2 is converted into conditioned PPG voltage
signals at outputs at nodes B and B', respectively. These
conditioned PPG voltage signals are provided to microcontroller 26
for digitizing and analysis.
[0133] Microcontroller 26 (FIG. 2) may be any commercially
available programmable device such as a Mitsubishi USB
microcontroller (available from Mitsubishi Semiconductors, Inc. of
Japan), although it should be understood that any type of logic
circuit with similar operating functions (particularly one which
has a USB interface and which includes an on-board
analog-to-digital converter) can be utilized. Storage of program
instructions and other static data is provided by a read only
memory (ROM) 40, while storage of dynamic data is provided by a
random access memory (RAM) 42. Both memory units 40 and 42 are
controlled and accessed by microprocessor 25. On board
analog-to-digital converter A/D 44 (10 bit, 5 channel input) is
used to convert the conditioned PPG signals at B and B' into time
sampled digital signals which are then provided to processing
device 14. Also, all of the circuitry of signal conditioner module
24 is provided with a 5 volt source from the USB line of
microcontroller 26.
[0134] Microcontroller 26 is also programmed to control the
operation of LED, and LED.sub.2 of PPG sensor 12 for optimal sensor
operation. Microcontroller 26 is programmed to generate digital
switching pulses to drive LED.sub.1 and LED.sub.2 of PPG sensor 12
alternately at a repetition rate of 1 KHz (i.e. each LED
accomplishes sampling at a rate of 1 KHz). It has been determined
that the sampling frequency should be 10 times the highest
frequency of interest. The conditioned PPG signal has frequency
components as high as 30 Hertz. However, 60 Hertz noise from
electrical sources in the environment necessitates sampling of the
signal at a high enough rate to ensure the effectiveness of the
associated noise filtering software of CPU 5.
[0135] By driving LED.sub.1 and LED.sub.2 alternately, it is
ensured that only one LED is turned on at any one time so that the
light signals are isolated from each other's photodiode. Also, both
LED.sub.1 and LED.sub.2 are periodically turned off to acquire a
signal used to correct for ambient light effects. Specifically,
ambient light effects are eliminated through subtraction of the
signal generated when the applicable LED.sub.1or LED.sub.2 is off.
Finally, the presence or absence of a finger on PPG sensor 12 can
be determined by turning on an LED for a brief period at a regular
time interval and determining whether the associated photodiode
detects any reflected light. This polling activity allows PPG
sensor 12 to be active only when necessary.
[0136] Thermistor 23 allows system 10 to specify the absolute
temperature at the skin surface. This additional information allows
for greater accuracy in correction of blood volume pulse contour
amplitude variations which are connected with temperature changes,
as will be discussed. An indirect measure of temperature is
obtained from the relationship between the amplitude of both the
raw PPG output and the blood volume pulse contour. The thermistor
allows more exact correlation. Such corrections will allow for more
accurate determinations of systolic and diastolic blood pressures
from the derived pressure pulse contour. As an additional feature,
system 10 allows the user to have a display of the room ambient
temperature on display 7 of processing device 14 at times when the
user's finger is not in contact with thermistor 23.
[0137] User input device 20 generally requires a small number of
inexpensive and commonly available components. Also, since
microcontroller 26 includes a USB interface, it is possible to
power user input device 20 completely from the computer processing
device 14 for additional space savings and product cost
economy.
[0138] FIG. 4 shows an improved alternative to elastic restraint 28
which can be used to force a finger into contact with PPG sensor
12. A conventional gas filled finger cuff bladder 29 within which
PPG sensor 12 is implanted, is shown surrounding the finger in a
circumferential manner. The epidermis 42, bone 44, and arteries 46
of a finger are shown enveloped within cuff bladder 29 that is
pressurized by a gas supply 48. The pressure of the gas within the
bladder can be monitored and used by microcontroller 24 in
association with pulse contour analysis data to more accurately
predict absolute values for blood pressure.
[0139] Specifically, the conventionally known `unloading` technique
described by J. Penz in U.S. Pat. No. 4,869,261 to Penaz et al. and
used commercially in the Finapres system manufactured by Ohmeda
involves the measurement of the size of the artery 46 when the
blood pressure within it is the same as the external pressure
imposed by the inflatable cuff bladder 29 that has been placed
around the finger. Processing device 14 will then compute blood
pressure measures based upon the PPG signal and upon the pressure
in the cuff bladder 29 while the artery is maintained in an
unloaded condition. In this way, the systolic, mean and diastolic
pressure can all be determined.
[0140] FIG. 5 shows another possible configuration of system 10
wherein processing device 14 is a PDA (e.g. Palm Pilot.TM.) having
PPG sensor 12 interfaced therein. PPG sensor 12 could be directly
integrated into the shell of the PDA processing device 14.
Alternatively, PPG sensor 12 could be implemented within a PDA
accessory card or device, or adapted to interface with the PDA
processing device 14 as an external wearable device. In the latter
case, it would be possible for a user to wear a wearable user input
device 12 such that blood volume pulse signal information could be
collected by the PDA processing device 14 over the course of a day.
It would be possible to arrange for periodic download of recorded
volume pulse contour signal information collected by user input
device 12 to processing device 14 and/or to Web site server 16
through processing device 14 over the communication network 18.
[0141] Further embodiments of the invention whereby PPG sensor 12
and processing device 14 are integrated together into a single unit
with a compact design are also contemplated as processing speed and
device memory increase as physical dimensions decrease. For
example, it is likely that PPG sensor 12 and processing device 14,
and all of its associated functionality, could feasibly be
incorporated into a wrist watch device in the foreseeable future.
It is contemplated that PPG sensor 12 could be integrated together
with a computing means, wireless transmission means (e.g. well
known convention radio frequency techniques as well as emerging
radio frequency communication protocols such as the BlueTooth.TM.
standard) and a battery in a small (e.g. 2 cm.sup.2) component that
would adhere to a body skin area for extended periods of time (e.g.
weeks) and would transmit data to a remote computing device on a
continuous basis.
[0142] FIG. 6 shows how PPG sensor 12 could be associated with the
user's earlobe 15 instead of the user's finger. As discussed, it is
well known that the reflective wave originating in the aorta has a
significant presence in the volume pulse contour obtained from a
fingertip, ear or other points on the surface of the body. As is
conventionally known, the volume pulse signal acquired from the ear
lobe, like the finger, is similar to that acquired from the carotid
artery. Specifically, it is contemplated that PPG sensor 12
operating in transmission mode could be implanted in a "clip"
device 17 which would provide for skin contact between PPG sensor
12 and a user's earlobe 15. This embodiment would provide analogous
pulse volume signal information from which various cardiovascular
and respiratory indices could be obtained, while allowing for hands
free functionality.
[0143] It should also be understood that PPG sensor 12 can also
consist of a single LED for reasons of product economy. However,
while such a configuration can be used to determine a number of
useful cardiovascular indices based on a time analysis of a single
pulse waveform, it does not allow for the determination of other
useful physiological signals, such as blood oxygen saturation, as
will be described.
[0144] It should be understood that the light emitter(s) in PPG
sensor 12 could also be a laser diode, which have the advantage of
producing a well collimated beam of light. This characteristic
would be advantageous to system 10 when measuring the time it take
a pulse signal to travel from one light source to the next. With
narrower beams of light, the photosensing elements are able to
resolve the signals from each light source with greater precision.
Also, while it is preferred to operate PPG sensor 12 in reflective
mode, it would be possible to operate PPG sensor 12 in the
transmission mode by making suitable alterations to the sensor's
configuration.
[0145] FIGS. 7A to FIG. 7G illustrate the striking variation in
shape of the arterial pressure pulse contour as measured throughout
the human body. As shown in FIG. 7A, the arterial pulse contour
obtained from the foot is almost completely lacking the additional
peak originating from the effects of the reflected wave as seen at
the wrist as shown in FIG. 7B. FIG. 7C shows the contour at the
brachial artery, FIG. 7D shows the contour at the auxiliary artery,
FIG. 7E shows the contour at the carotid artery, FIG. 7F shows the
contour at the axillary artery and FIG. 7G shows the contour at the
femoral artery. The differences in the contour of the pulse wave at
different points of the human body is due to both changes in the
impedance of the arterial tree and because of the effects of
reflected waves.
[0146] As the heart contracts, a volume of blood is ejected into
the aorta, the large artery leading from the heart. The elastic
walls of the aorta expand in response to the volume of blood
introduced. A wave is initiated in the walls of the aorta by this
expansion. This wave in the walls of the aorta travels about ten
times faster than the blood itself. This wave travels down the
arterial `tree` as the aorta branches and divides into smaller and
smaller arterial vessels until reaching the capillaries. This wave
produced by contraction of the heart is generally called the
systolic wave. A second pulse wave emanates from the heart with the
forceful closure of the aortic valve. As this valve closes, the
rebounding valve leaflets create a wave termed the dicrotic wave.
The systolic and dicrotic waves are referred to as primary pulse
waves.
[0147] The primary pulse waves are partially reflected when they
encounter areas of impedance mismatch in the arterial system, and
the reflected waves travel back towards the heart. These areas of
impedance mismatch can arise through branching, changes in diameter
or elasticity of an arterial vessel. The systolic and dicrotic
waves both produce a set of reflections that propagate through the
arterial system, namely the systolic and dicrotic reflected waves.
Reflected waves generated in the extremities are rapidly damped as
they progress from smaller to larger blood vessels. Reflected waves
generated in the aorta, especially the abdominal aorta are able to
travel in a retrograde fashion without significant damping. The
abdominal aorta at the level of the kidneys serves as an important
reflecting site and produces systolic and dicrotic reflected waves.
The abdominal aortic reflected waves appear prominently in the
blood volume pulse contour as observed in locations above the
abdominal aortic reflection site.
[0148] In addition to the reflected waves originating in the
abdominal aorta, wave reflections occur at the entrance to the head
circulation and in the small blood vessels within the fingertip,
earlobe and other potential sensing sites. It is possible to
differentiate between the reflected waves of differing origin
because of the difference in time each takes to reach a certain
location and the differing amplitudes of the reflected waves.
[0149] The characteristics of the aortic reflected wave are strong
indicators of cardiovascular health. The speed with which the
aortic reflected wave travels along the aorta varies with changes
in aortic compliance and blood pressure, both of which also affect
aortic pulse wave velocity. The aortic reflected wave travels more
quickly as blood pressure increases and as aortic compliance
decreases. It is also noteworthy that blood pressure and aortic
pulse wave velocity rise and fall with respiration. Accordingly, by
appropriately analyzing the aortic reflected wave, it is possible
to obtain cardiovascular and respiratory information about an
individual user, as will be discussed.
[0150] FIG. 8 is a plot of a typical conditioned PPG pulse contour
signal received by processing device 14 from the user input device
20. As illustrated, the PPG pulse contour consists of three peaks,
namely a peak representing the systolic maximum (A), the reflected
wave maximum (B), and the dicrotic notch (C) which represents the
aortic valve closure. The PPG pulse contour also consists of the
upstroke point (onset of systole at D) and end diastole (E).
[0151] Typically, it is not so easy to identify these various
characteristic points (e.g. reflected wave maximum) from the PPG
pulse contour signal on the basis of visual inspection alone. This
is due to the fact that the interaction between primary and
reflected waves obscures PPG wave detail preventing clear
extraction of accurate timing and amplitude relationships between
the primary and reflected waves. In order to extract the signal
related to the aortic reflected wave from the raw PPG signal,
several processing steps must be followed.
[0152] The raw PPG signal is affected by all factors which
determine tissue blood volume. Because the arterial pulse wave, of
which the aortic reflected wave is a component, originates from
arterial blood vessels, it is necessary to isolate the signal
originating from arterial blood vessels. This signal is rapidly
pulsatile, relative to other physiological signals contained in the
raw PPG signal. There are less rapidly pulsatile signals such as
respiratory related cyclic volume changes, temperature related
volume changes, autonomic nervous system induced changes in blood
vessel tone leading to very slow volume changes as well as changes
in volume according to position. Because the arterial pulsations
are higher in frequency than the other signals related to blood
volume changes, the arterial pulsations can be isolated by
filtering out all fluctuations in blood volume below approximately
0.5 Hertz. However, if the respiratory rate is rapid, the cutoff
frequency must be raised.
[0153] The rapidly pulsatile signal corresponds to the arterial
compartment. Each time the heart beats, this compartment undergoes
an expansion and contraction as the heart pulse wave passes
through. This signal is conventionally called the volume pulse
contour which, in the finger is termed the digital volume pulse
(DVP). The signal from the arterial compartment will be affected by
changes in blood pressure and temperature. As temperature
increases, the amplitude of the volume pulse contour increases. As
blood pressure increases, the amplitude of the volume pulse contour
increases.
[0154] The raw PPG signal also contains a DC (or nonpulsatile)
signal component which varies with temperature but which does not
vary with changes in blood pressure. Observation of the
fluctuations in this DC component allows for correction of
temperature related changes and allows the amplitude of the
arterial volume pulse contour to be corrected for variation in
temperature. For example, it would be possible to determine the
impact of temperature change by following the changes in the raw
PPG signal after the user has cooled his/her finger in a glass of
ice water as the finger rewarms. It would also be possible to
adjust the DC level of the PPG signal to compensate for change in
temperature.
[0155] Generally, removing the DC or nonpulsatile signal from the
conditioned PPG signal results in a signal that is related to
pulsatile changes in finger blood volume and also to vascular and
respiratory effects. Low pass filtering the conditioned PPG signal
removes the faster signal components related to heart beat (i.e.
the highly pulsatile signals) and the resulting slowly pulsatile
signal can be used to track heart rate and respiratory related
physiological characteristics. The exact frequency needed to
isolate heart and respiratory signals varies with changes in heart
rate and respiratory rate and it is necessary to adapt the cutoff
frequency to the heartbeat and respiratory rate of a particular
user.
[0156] For example, it has been observed that a relatively clear
slowly pulsatile signal can be obtained by filtering out signal
components from a typical conditioned PPG signal which have a
frequency of 0.5 Hertz or higher. High pass filtering the
conditioned PPG signal removes the slower signal components related
to respiration (i.e. the slowly pulsatile signals) and roughly
isolates the highly pulsatile signal (i.e. the DVP signal) which
reflects blood volume changes related to heartbeat. The DVP signal
can be analyzed to produce a plurality of signals related to the
state of the cardiovascular system as well as respiratory function
as will be described.
[0157] Also, it has been observed that varying finger pressure and
finger motion while a user's finger is positioned on PPG sensor 12
results in fluctuations in the amplitude of the derived
nonpulsatile and pulsatile signals. Pressure exerted on the
fingertip causes a decrease in the volume of blood in the tissues
of the fingertip. Tilting the body to one side or another will also
produce changes in the amplitude of the nonpulsatile and pulsatile
portions of the PPG signal. Rapid fluctuations in the PPG signal
which relate to mechanical disruption of the skin-PPG interface can
be compensated by conventionally known artifact reduction
techniques which substantially decrease the distortion of the
volume pulse contour caused by movements of the finger and/or PPG
sensor 12.
[0158] Analysis of the DVP is difficult because of the overlapping
of the various primary and reflected waves. Generally, the systolic
and the dicrotic waves and the reflections of these waves
travelling within the arterial system form the DVP signal. The
systolic wave, the systolic reflected wave, the dicrotic wave and
the dicrotic reflected wave interact to obscure the peak of the
systolic wave as well as the foot and the peak of the systolic and
dicrotic reflected waves. In order to properly characterize the
DVP, analysis of the waves contributing to the shape of the DVP
must be undertaken. Signals in the DVP, related to the systolic and
dicrotic reflected waves, provide a rich source of information
about the health of the cardiovascular system and other internal
organs.
[0159] Referring to FIG. 9A, there is shown an overview of the
process 100 of DVP pulse contour analysis according to the present
invention. FIG. 9A is representative of the process of DVP pulse
contour analysis and also the underlying computer programs of
system 10. Specifically, the execution of process 100 is directed
under program control by microcontroller 26 of user interface
device 20 and CPU 5 of processing device 14 and associated computer
peripherals.
[0160] Referring now to FIGS. 1, 2, 3, and 9A, process 100 begins
with obtaining a raw PPG signal from photodiodes PD.sub.1 and
PD.sub.2 (102) from PPG sensor 12 and conditioning/digitizing the
raw PPG signal (104) using signal conditioning module 24 and
microcontroller 26 of user input device 20. The CPU 5 of processing
device 14 then effects the high pass filtering of the conditioned
PPG signal (106) to remove the non-pulsatile and slowly pulsatile
components of the PPG signal to obtain the DVP signal.
[0161] Before beginning analysis of the DVP signal, it is important
to correct the DVP with regard to temperature variation. The DVP
signal can be corrected by CPU 5 of processing device 14 for
temperature related variations (108) using temperature calibration
data from thermistor 23 of user input device 20. Since system 10
can specify the absolute temperature at the skin surface it is
possible to use this absolute value to compensate for variations in
the DVP signal due to temperature. In this way, a more accurate
determination of systolic and diastolic blood pressures can be
obtained from the DVP signal as will be explained.
[0162] As shown in FIG. 9B, it is possible to achieve temperature
correction using the raw PPG signal with a correction factor that
can be calculated for a particular user or predetermined for
general application. The relationship between change in PPG
amplitude and change in the DVP amplitude can be represented by the
mathematical expression:
.DELTA.PPG=K (.DELTA.DVP),
[0163] where K is a constant. Accordingly, a value for K can be
determined by subjecting a finger to a change in volume independent
of blood pressure. CPU 5 of processing device 14 can be
appropriately programmed to correct the DVP amplitude to compensate
for changes in blood volume that are unrelated to blood pressure
effects.
[0164] Specifically, CPU 5 of processing device 14 can be
programmed to instruct the user to cool his or her finger (i.e. by
placing it on an ice cube for a period of time) (116) and then to
position his or her finger over PPG sensor 12 of user input device
20 (118). CPU 5 of processing device 14 then determines the
amplitude of the raw PPG signal (at node A of conditioning circuit
24 of FIG. 3) and the amplitude of the DVP signal (discussed above
in relation to step 106 of FIG. 9A) at sample times T.sub.1,
T.sub.2, . . . , T.sub.n as the user's finger warms up (120). The
changes in amplitude of the raw PPG signal between sample times
T.sub.1, T.sub.2, . . . , T.sub.n (or .DELTA.PPG.sub.1 for i=1 to
n-1) and the changes in amplitude of the DVP signal between sample
times T.sub.1, T.sub.2, . . . , T.sub.n (or .DELTA.DVP.sub.i for
i=1 to n-1) are calculated (122). Values K.sub.1 to K.sub.n-1 are
calculated according to the relation
K.sub.i=.DELTA.PPG.sub.i/.DELTA.DVP.sub.1 for i=1 to n-1 (at 124).
Finally, the average of the values K.sub.1 to K.sub.n-1 is
calculated to determine the value of K for the user.
[0165] In this way, the relationship between the amplitudes of the
raw PPG signal and the DVP signal can be used to determine a
working constant value for K can be determined. In this way it is
possible to use the DVP signal to obtain a more reliable reading
for blood pressure values. It should be noted that temperature
correction is not necessary for cardiovascular indices that are
amplitude independent. Indices which are based on relative
measurements made on the DVP contour at different points in time or
at the same point on two separate DVP contours will not dependent
on absolute determination of DVP amplitudes.
[0166] CPU 5 of processing device 14 then conducts pulse contour
analysis of the DVP signal (110) to obtain characteristics of the
systolic wave and the systolic reflected wave as will be discussed
in detail. CPU 5 of processing device 14 converts these
characteristics into cardiovascular indices and basic
cardiovascular and respiratory and neurological physiological data
is calculated (112). Finally, CPU 5 of processing device 14 stores
the physiological data in memory for future retrieval, displays the
data to user on display 7 and transmits the data over communication
network 18.
[0167] Several methods of pulse contour analysis are contemplated
by the present invention. As previously discussed, various
characterizations of the systolic reflected wave discussed in the
literature fail to accurately identify the systolic reflected wave
peak accurately. Using the methods of the present invention, it is
possible to characterize the systolic reflected wave (e.g. the
systolic reflected wave peak) from within the DVP signal.
[0168] First, as shown in FIGS. 10A to 10E, it has been determined
that by calculating the first, second and the fourth derivatives of
the DVP signal, it is possible to identify a number of critical
points related to the systolic wave and the systolic reflected
wave. Specifically, FIG. 10A shows the DVP signal, FIG. 10B shows
the first derivative of the DVP signal, FIG. 10C shows the second
derivative of the DVP signal, FIG. 10D shows the third derivative
of the DVP signal, and FIG. 10E shows the fourth derivative of the
DVP signal.
[0169] As shown in FIG. 10B, in known manner, the pulse relative
maximum and minimum points correspond to the zero crossings of the
first derivative curve. The maximum point of the first derivative
curve corresponds to the point of maximum pulse slope, that is, the
point in early systole at which the pulse is rising most steeply to
its first peak. The point of systolic onset (at D), which is also
referred to as the wave foot, corresponds to the first
negative-to-positive zero crossing (at D') which precedes the first
derivative maximum point. The systolic peak (at A) can also be
identified on the DVP' signal as the time of the zero crossing from
positive to negative of the first derivative (at A') after the peak
of the first derivative.
[0170] Once the point of systolic onset is located, the maximum
peak for the reflected wave (at B) can be determined from the DVP
signal. In order to positively identify the maximum peak for the
reflected wave (at B), the fourth derivative curve must be
examined. Specifically, it has been determined that the second zero
crossing from negative-to-positive (at B') of the fourth time
derivative of the DVP signal is a consistent indicator of the
maximum peak of the reflected wave pulse (at B) as shown.
[0171] It is noteworthy that many authors of scientific literature
related to the observation of the augmentation index endeavour to
identify what is terms the `inflection point` on the aortic
pressure pulse contour. In contrast, the present invention is
directed at identifying the slope change associated with the
maximum of the reflected wave, as it has been observed that the
maximum point of the reflected wave has a stronger correlation with
the aortic reflected wave signal. Because of the aortic reflected
wave signal's ability to propagate in a retrograde fashion with
little attenuation, it will always substantially contribute to the
maximum of the slope change following the inflection point. In
contrast, the inflection point is more likely to be influenced by
reflected wave signals other than the aortic reflected wave
signal.
[0172] However, it should be noted that a number of points on the
fourth derivative of the DVP signal can be used to determine
critical points on the aortic reflected wave contour. For example,
it has been observed that the second zero crossing from positive to
negative of the fourth derivative of the DVP signal can be used to
identify the inflection point on the aortic reflected wave.
[0173] From observation of a large number of clinical cases, it has
been experimentally confirmed that while certain changes in slope
of the aortic reflected wave contour can be identified in the first
and third derivatives of the DVP signal, there are a significant
number of cases where all trace of the reflected wave maximum is
lost or completely obscured by the primary systolic pulse wave
within the DVP signal. These cases tended to be in older patients
where the aortic reflected wave was closer to the primary systolic
pulse wave than in younger patients. It was determined that by
taking the fourth derivative, it was possible to consistently
determine the maximum of the aortic reflected wave signal within
the DVP signal.
[0174] Second, as shown in FIGS. 11A to 11D, it has been determined
that it is also possible to identify a number of critical points
related to the systolic wave and the systolic reflected wave by
appropriately bandpass filtering the DVP signal. For illustration
FIG. 11A shows the DVP signal, FIG. 11B shows the first derivative
of the DVP signal, FIG. 11C shows the fourth derivative of the DVP
signal, and FIG. 11D shows the result of bandpass filtering the DVP
signal using a bandpass filter with cutoff frequencies of 6 and 20
Hertz. It has been observed that the reflected wave signal is
strongest at 4 to 8 Hertz. 6 Hertz lies in the middle of this
range. 20 Hertz is low enough to eliminate high frequency noise and
high enough to observe crucial high frequency reflected wave
components.
[0175] As shown in FIGS. 11A, 11C and 11D, the maximum peak for the
systolic reflected wave (at B) can be determined from the DVP
signal from either the fourth derivative or the band passed DVP
signal. By bandpass filtering the DVP signal, a signal with zero
crossing points that are closely associated with those of the
fourth derivative of the DVP signal is produced. Specifically, the
second zero crossing from negative-to-positive (at B') of the
fourth time derivative of the DVP signal occurs at the same time as
the second zero crossing from negative-to-positive (at B") of the
bandpass filtered DVP signal. Accordingly, the DVP signal band
passed in this fashion can be utilized to identify the systolic
reflected wave peak (at B). It has been determined that a
limitation of this method is that the bandpass filter introduces a
phase delay into the DVP signal. Consequently, it is necessary to
adjust the DVP signal to compensate for the phase delay.
[0176] While the above methods allow for the accurate
identification of the foot of the systolic wave pulse and the
systolic wave peak, it is preferable to use the respiration
frequency extraction technique of the present invention to obtain
an accurate estimate of the entire signal contour shape of the
reflected wave components originating in the abdominal aorta, as
will be described. The shape of the aortic reflected wave is a rich
signal that varies with changes in function of the heart, lungs,
and organs of the abdominal vascular bed and allows for
determination of related diagnostics. Also, once the aortic
reflected wave contour is obtained, it is possible to extract
accurate representations of the systolic wave and the systolic
reflected waves from the DVP signal as will be explained.
[0177] The interaction between primary and reflected waves obscures
wave detail preventing the determination of exact timing and
amplitude relationships between primary and reflected waves. Also,
the shape of the DVP changes on a beat to beat basis due to changes
in the timing and amplitude of the reflected wave components
associated with respiration. With inspiration, blood pressure falls
and the aortic reflected waves will arrive later at the finger and
with smaller amplitude. As blood pressure decreases, the pulse
transit time increases. This inverse relationship between blood
pressure and pulse transit time causes the reflected wave signal to
appear earlier or later in the DVP signal.
[0178] Due to the fact that the reflected wave contour is shifting
back and forth within the underlying DVP signal, it is possible to
use signal extraction techniques to remove the components which do
not vary with breathing. By removing the components associated with
respiration from the DVP signal which otherwise interact and
obscure each other's characteristics, it is possible to ascertain
the shape of the isolated reflected wave signal within the
remaining components of the DVP and to determine the timing and
amplitude characteristics of the reflected wave. This information
can then be used for calculation of cardiovascular parameters such
as aortic pulse wave velocity.
[0179] Referring to FIGS. 12A and 12B, there is shown an overview
of the steps of the respiratory matrix filtering method 200 of the
present invention. This method is based on the observation that the
aortic reflected wave signal in the DVP signal shifts with
respiration due to changes in blood pressure associated with
respiration. That is, the reflected wave components of the DVP
signal originating in the abdominal aorta are characterized by a
transit time that varies with respiration. The change in blood
pressure that occurs with respiration induces changes in aortic
pulse wave velocity. These changes result in variations in the
aortic reflected wave transit time which in turn causes changes in
the position of the reflected wave within the DVP signal in
association with respiration. The DVP signal also changes with
respiration due to the effects of blood pressure and cardiac output
changes cycling with respiration. With inspiration, the blood
pressure falls causing a decrease in the DVP amplitude. The
respiratory matrix filtering method 200 eliminates respiratory
induced baseline and arterial volume changes from the DVP signal by
filtering out those components of the DVP signal that do not change
on a beat to beat basis (i.e. the DC components), in order to
isolate the aortic reflected wave.
[0180] The DVP signal is first high pass filtered above 0.5 Hertz
(202) to remove baseline fluctuations related to respiration. The
DVP signal is then smoothed (204) using a conventionally known
smoothing routine, (e.g. the Savitzky-Golay routine) in order to
smooth the signal, to eliminate noise and to interpolate between
sample data points. The individual DVP beats within the DVP signal
are then monitored and analyzed over a period of time. In
particular, the DVP signal is observed until M DVP beats (i.e.
BEAT.sub.1, BEAT.sub.2, BEAT.sub.3, ... BEAT.sub.M) have been
observed. The M DVP beats BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M are
sampled periodically at N sampling points (i.e. T.sub.1 to T.sub.N)
(206) as shown in FIGS. 12C, 12D and 12E to obtain corresponding
amplitudes (e.g. A.sub.11, A.sub.12, A.sub.1Nand A.sub.M1,
A.sub.M2, A.sub.MN).
[0181] Typically 100 to 200 beats are observed by method 200 (i.e.
M has a value of between 100 and 200). Since a typical DVP beat has
a duration of 1.0 seconds and since samples are taken every
millisecond, roughly 1000 samples of each DVP beat are taken,
depending on the heart rate of the user. Time is measured in
increments of 1 millisecond and amplitude of the DVP beats is
measured in increments of 1 millivolt. Amplitude of the DVP beats
typically falls within the range of 0 and 4000 millivolts depending
upon the level of voltage amplification of the PPG signal provide
by signal conditioner module 24.
[0182] The M individual DVP beats BEAT.sub.1, BEAT.sub.2, to
BEAT.sub.M are then synchronized. This is accomplished by first
identifying the initiation of each beat (i.e. the foot of the
systolic pulse wave) using signal analysis technique steps shown in
FIG. 12B (208). Specifically, the initial time sample point,
T.sub.1 is determined for each of the M individual DVP beats
BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M, by calculating the first
derivative of each DVP beat BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M
(220) (not shown).
[0183] For each DVP beat BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M, the
slope of the sampling data points comprising the first 10 percent
of the rising limb of the first derivative leading to the peak for
each DVP beat BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M, is
extrapolated backwards to determine the zero crossing point on the
time axis of the plot (222). It has been observed that this zero
crossing point represents the initiation of the DVP beat with
reasonable accuracy. This approach is believed to provide superior
results than zero crossing detection using conventional sampling
techniques for several reasons. First, it is difficult to identify
accurately the zero crossing point when low sampling speed is
utilized. By extrapolating a line derived from the slope of the
rising limb down to the time axis of the plot, it is possible to
accurately pinpoint the precise time location of the zero crossing
point. Second, by using the first 10 percent of the rising limb of
the DVP beat, it is possible to avoid reflection induced
perturbations.
[0184] Each DVP beat BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M is then
time synchronized by measuring the amplitude of the M DVP beats
BEAT.sub.1, BEAT.sub.2 to BEAT.sub.M at T.sub.1 (224), normalizing
the M beats so that all DVP beats are zero at T.sub.1 and aligning
the DVP beats at the time T.sub.1 for each beat (226). It has been
observed that the DVP signal amplitude shifts on a beat to beat
basis as a result of shifts in blood pressure, finger arterial
blood volume and shifts in the timing of the aortic reflected curve
signal in association with respiration.
[0185] Once a train of DVP beats BEAT.sub.1, BEAT.sub.2, to
BEAT.sub.M is isolated and synchronized, the amplitude values for
the DVP beats BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M are arranged in
Spreadsheet A (210) in columns of sampling times (T.sub.1, T.sub.2,
. . . , T.sub.N) as shown in FIG. 12F. For example, the amplitude
of all the DVP beats BEAT.sub.1, BEAT.sub.2, to BEAT.sub.M at each
beat's T.sub.1 is placed in the first column of Spreadsheet A (note
that the amplitudes at each beat's T.sub.1 have all been normalized
to zero), the amplitude of all of the DVP beats BEAT.sub.1,
BEAT.sub.2, to BEAT.sub.M at each beat's T.sub.2is placed in the
second column, and so on. T.sub.per is the period between derived
samples and is generally equal to the actual sampling interval.
Thus, T.sub.1+T.sub.per=T.sub.2 . . . T.sub.N=T.sub.N-1+T.sub.per
where N is the total number of samples per beat (as discussed
before, T.sub.peris typically 1 millisecond). The last sampling
period will correspond to the first instance of a beat in the
series entering a new systolic period as identified using the first
derivative of the DVP beat as discussed above.
[0186] Columns corresponding to each sampling time are filled with
the amplitudes of all beats at that sampling time. By treating the
series of values in each column as a new signal SYNC.sub.T where T
is the sample time, it is possible to use filtering algorithms to
extract components from the signals SYNC.sub.T (for T=1 to N). As
discussed above, the aortic reflected wave shifts back and forth
within the DVP signal with respiration (i.e. at the respiratory
frequency). Accordingly, it is possible to observe the aortic
reflected wave by looking only at those parts of the DVP signal
which vary on a beat to beat basis. The portions of the signals
SYNC.sub.T that do not vary on a beat to beat basis are the DC and
nonpulsatile components which do not vary with blood pressure.
[0187] By appropriately bandpass filtering the signals SYNC.sub.T
in the range of the user's respiratory frequency, it is possible to
retain those components in the DVP signal that vary at a rate
associated with respiration (i.e. those that are related to the
aortic reflected wave). Finally, it should be noted that the signal
distortions associated with motion artifact will generally occur at
a higher frequency than the respiratory rate which suggests that
this form of bandpass filtering around the respiratory frequency
will also serve to produce a noise free respiration contour.
[0188] The beat sample data points of spreadsheet A is obtained
from the continuous DVP beat contours as shown graphically in FIG.
12G. Each set of beat data samples for a particular sample point
T.sub.T (for T=1 to N) (i.e. each signal SYNC.sub.T) are then
separately re-graphed for interpolation purposes (212).
Specifically, signal SYNC.sub.5 shown in FIG. 12H, is obtained by
graphing the sample data obtained from each DVP beat BEAT.sub.1,
BEAT.sub.2, to BEAT.sub.N at sample point T.sub.5. The sample
points for each DVP beat will be related to the absolute time in
milliseconds from sample point T.sub.1 of BEAT.sub.1 as shown on
the time axis of FIGS. 12G and 12H. Also, the time axis of the
graphs shown in FIGS. 12G and 12H, represents time measured
continuously from time T.sub.1 of BEAT.sub.1 (or T.sub.11) in
milliseconds. The interval between sample times (e.g. between
T.sub.11 and T.sub.12 etc.) will be the same as in spreadsheet A
(FIG. 12F). As shown, there will be many empty points between the
sample points. By using a conventionally known polynomial curve
fitting algorithm, it is possible to interpolate between sample
points and to produce an approximately fitted curve for each signal
SYNC.sub.T as shown in FIG. 12H.
[0189] Once the curve of each sample point for each beat
BEAT.sub.1, BEAT.sub.2, to BEAT.sub.N has been filled using
interpolation techniques, these curves are bandpass filtered using
a filtering algorithm (214). Without interpolation, filtering of
the widely separated points would create sharp transients that
would corrupt the result. The bandpass filter has a center
frequency that centres around the respiratory frequency of the
user. In general, the lower cutoff of 0.1 Hertz and an upper cutoff
frequency of 0.5 Hertz have been used advantageously. However, if
it is determined that a particular individual user's respiratory
rate is outside of these limits, the cutoff frequencies of the band
pass filter can be adjusted. By bandpass filtering the signals
SYNC.sub.T, amplitude components of the DVP beats BEAT.sub.1,
BEAT.sub.2, to BEAT.sub.M which do not vary at or about the
respiratory rate are filtered out leaving a signal which will
predominantly contain the aortic reflected wave (which varies at a
frequency that falls within the bandpass filter corner
frequencies).
[0190] Once the signals SYNC.sub.T have been band pass filtered,
the data from the cells originally occupied with data prior to
interpolation, is returned to the associated column of spreadsheet
A. All DC and fast AC components of the signal will have been
removed and the only remaining signals will be related to
respiratory variation. The aortic reflected wave may then be
separated from other minor components using conventional analysis
techniques. It will be possible to examine the rows of data
corresponding to each beat. Graphing the data will reveal the
contour of the aortic reflected wave. The band pass filtered data
from a series of beats could also be displayed to the user in a
waterfall mode. With each separate bandpass filtered DVP beat
layered sequentially, the aortic reflected wave could be seen to
move cyclically towards and away from T.sub.1 within each DVP
beat.
[0191] The aortic reflected wave has a parabolic shape most evident
at its peak when seen in the signal obtained using the respiration
matrix filtering method 200. Extrapolation of the parabolic aortic
reflected wave from the shape will allow for precise definition of
the initial zero crossing point of the parabola. This point
corresponds to the appearance of the aortic reflected wave and can
be used to precisely define the transit time of the aortic
reflected wave. With knowledge of the distance between the heart
and the reflecting site in the abdomen (an estimate can be obtained
based on a user's height), the aortic pulse wave velocity and the
aortic compliance for a user can be calculated using the
conventional relationship between velocity, distance and time. The
distance from the heart to the reflecting site is about the
distance to the origin of the renal arteries.
[0192] It is contemplated that a number of other promising wave
analysis techniques could be used to isolate the aortic reflected
wave from the DVP signal. First, the technique of homomorphic
analysis could be used to obtain the curve of the aortic reflected
wave as discussed in the text "A Case-study Approach to Solve
Problems in Biomedical Signal Analysis", Rangaraj, M, Rangayyan
(IEEE Press, New Jersey: 2000), Chapter 4, pgs. 128 to 136.
Specifically, the DVP signal can be though of as a prime impulse
and a train of echoes superimposed on a dicrotic impulse and
another associated train of echoes. These echoes can be
characterized using the conventionally known technique of
homomorphic analysis. This technique is based on the premise that
the shape or morphology of the echoes are similar in shape to the
primary impulse. It has been observed that this technique is
proficient at isolating the primary impulse (i.e. the systolic wave
pulse).
[0193] Second, the aortic reflected wave pulse could be obtained
using conventionally known adaptive filtering techniques. It would
be possible to use adaptive filtering techniques to isolate the
components of the DVP signal that vary in association with
respiration. Finally, it is contemplated that since the aortic
reflected wave components have characteristic frequency
distribution which differs from that of the primary (systolic)
wave, it would be possible to use time-frequency analysis to
isolate the aortic reflected wave components and
characteristics.
[0194] Once the aortic reflected wave contour has been obtained by
respiratory frequency extraction of the DVP signal as discussed
above, the systolic reflected wave as differentiated from the
dicrotic reflected wave can be analyzed to obtain information
regarding short and long term changes in the cardiovascular system
and other organ systems. The systolic reflected wave
characteristics are determined by its passage through the vascular
components of the abdominal organs and the large blood vessels of
the cardiovascular system, and accordingly are a rich source of
cardiovascular information for the user as will be discussed. Also,
as discussed, by subtracting the isolated reflected wave signal
from the overall DVP contour, it is possible to better identify the
systolic and dicrotic waves, since the systolic peak is often
obscured by the reflective wave.
[0195] The use of the derivative, high pass filtering, and
respiratory matrix filtering techniques described above can be used
to determine a variety of conventionally known indices from the
systolic wave and the systolic reflected wave which are useful
correlates of various cardiovascular parameters, including mean
blood pressure, respiratory function, and aortic pulse wave
velocity.
[0196] These indices all vary on a beat-to-beat basis with changes
in aortic transit time of the reflected wave from a source in the
abdomen as previously discussed. They also vary with mean blood
pressure and respiration, and accordingly all of these indices can
be used to track mean blood pressure and to synthesize the
respiratory signal. As previously discussed, the amplitude of the
DVP signal is highly variable as it is extremely sensitive to
ambient light, temperature, mechanical and other environmental
disturbances. Accordingly, it is necessary to perform analysis of
the DVP signal by making relative measures of various amplitudes
and timing delays of components within the DVP signal instead of
absolute measures.
[0197] Referring back to FIG. 8, several relevant cardiovascular
indices which can be determined by system 10 are based on
identification of the systolic foot (at D), the systolic peak (at
A) and the systolic reflected wave peak (at B) of the DVP signal.
These points can be identified using the three approaches discussed
above.
[0198] Specifically, referring back to FIGS. 10A and 10B, the
systolic foot (at D) is identified as the time of the zero crossing
of the first derivative of the DVP signal (at D') preceding the
first derivative maximum. The systolic peak (at A) is identified as
the time of the zero crossing from positive to negative of the
first derivative (at A') after the peak of the first derivative.
Now referring to FIGS. 10A and 10E, the reflected wave peak (at B)
is identified as the time of the second zero crossing from negative
to positive of the fourth derivative of the DVP signal (at B').
[0199] As previously discussed, the high pass filtered DVP signal
can be used in place of the fourth derivative of the DVP signal to
determine the systolic and reflected wave peaks. Also, as
discussed, the location of the systolic wave foot the systolic wave
peak and the systolic reflected wave peak can be determined through
the use of the respiratory frequency extraction technique discussed
above to extract the aortic reflected wave.
[0200] It has been determined that three indices, namely
.DELTA.T.sub.Ref, INDEX.sub.Ref, and INDEX.sub.2nd Deriv are useful
correlates for many well-known cardiovascular parameters such as
mean blood pressure and aortic pulse wave velocity. These indices
can be easily determined from the various peak and foot
measurements of the DVP signal discussed above and which are shown
on FIG. 13 in association with the following indices:
[0201] 1. .DELTA.T.sub.Ref is a measure of the time between the
foot of the systolic wave pulse (at D on FIG. 13) and the peak of
the systolic reflected wave pulse (at B on FIG. 13) in the DVP
signal. The time difference between the foot (or initiation) of the
systolic pulse and the maximum peak of the reflected wave is
strongly representative of the pulse transit time of the reflective
wave as it travels back from the heart to the reflection site in
the trunk and back to the subclavian artery. Accordingly, it is
possible to determine aortic pulse wave velocity from measured
values of the pulse transit time by correcting for height (i.e.
approximate travel path), as previously discussed.
[0202] While it is also possible to measure the time between the
peak of the systolic wave pulse and the peak of the systolic
reflected wave, it is preferable to measure the time from the foot
of the systolic wave pulse as the beginning of the systolic pulse
is relatively free of distortion from reflected waves.
[0203] 2. INDEX.sub.Ref or the reflected wave index, is analogous
to the conventional pressure pulse augmentation index. The
conventional pressure pulse augmentation index is the ratio of the
main systolic peak to the amplitude of a portion of the pressure
pulse contour associated with the aortic reflected wave.
INDEX.sub.Ref is the percentage ratio of the amplitude of the DVP
signal at the reflected wave peak (at B) (i.e. height "b" on FIG.
13) relative to the amplitude of the DVP signal peak (at A) (i.e.
height "a" on FIG. 13). Accordingly, INDEX.sub.Ref=b/a*100% (FIG.
13). While the augmentation index is conventionally derived from
the proximal aortic pressure pulse contour, the augmentation index
derived from the DVP signal will also be correlated with aortic
pulse wave velocity and other cardiovascular parameters. It should
be noted that if the reflected wave peak occurs prior to the
systolic peak, the index would be negative.
[0204] 3. As shown in FIG. 14, INDEX.sub.2nd Deriv is derived from
the second derivative of the DVP signal (as shown in FIG. 10C). In
the second derivative there is an initial peak (at X) followed by a
deep trough (at Y) followed by a second peak (at Z). The ratio of
the height (d) of the second peak (at Z) relative to the distance
from the horizontal axis to the nadir or the depth (e) of the deep
trough (at Y), is related to the amplitude and timing of the
reflected wave. Accordingly, INDEX.sub.2nd Deriv is the percentage
ratio: d/e*100% (FIG. 14). Since the larger systolic wave precedes
the smaller systolic reflected wave, the closer the systolic
reflected wave peak is to the systolic wave peak, the greater the
amplitude of the systolic wave will be.
[0205] As disclosed in U.S. Pat. No. 4,432,374 to Osanai, second
derivative indices can be used to discern cardiovascular health.
Twice differentiated PPG signals are indicative of blood
circulation whose interpretation effectively leads to a diagnosis
of the entire circulatory system including early signs of
malfunction. Analysis of the second derivative of the DVP signal
allow for detection of presymptoms of arteriosclerosis, myocardial
infarction, cerebral apoplexy, subarchnoidal hemorrhage, etc. is
possible.
[0206] The extent of upward deflection of the DVP contour caused by
the systolic reflected wave depends on its proximity to the masking
influence of the larger systolic wave. A smaller upward inflection
of the systolic wave occurs if there is a relatively small delay
between the systolic and systolic reflected wave peaks. This will
result in the height (d) of the second peak (at Z) in the second
derivative being relatively less. The specific correlation between
INDEX.sub.2nd Derriv and the systolic reflected wave and thus the
aortic transit time of the reflected wave is useful in determining
various cardiovascular measures. INDEX.sub.2nd Deriv also
correlates well with beat to beat blood pressure and longer term
aortic pulse wave velocity changes.
[0207] As previously discussed, aortic pulse wave velocity is an
indirect but reliable measure of aortic compliance and a powerful
measure of cardiovascular health and relative risk. Once aortic
pulse wave velocity has been determined and the components of the
DVP contour have been identified, conventional methods can be used
to determine a number of diagnostic values including mean blood
pressure, blood pressure, respiratory rate and rhythm, sleep apnea,
and autonomic function, and aortic compliance as will be
described.
[0208] FIG. 15A illustrates how mean pulse amplitude of the DVP
signal can be determined. First, the DVP signal must be temperature
normalized and have respiratory variations removed, as previously
discussed. The area between such a DVP signal (R) and the diastolic
signal amplitude (S) is measured for the duration of a heartbeat
and that value is divided by the duration of the heartbeat or pulse
(T) as shown graphically in FIG. 15A. The mean pulse amplitude of
the DVP signal will fluctuate with blood pressure, that is, as
blood pressure rises, the DVP signal will show proportional
changes. Accordingly, it is possible to use the mean pulse
amplitude value of the DVP signal as a correlate of mean blood
pressure, and in this way blood pressure changes can be monitored
by system 10.
[0209] An accurate correlate of the pulse pressure (i.e. the
difference between systolic and diastolic pressure) can also be
derived from the maximum and the minimum excursion of the DVP
signal R. Thus, the combination of pulse wave velocity and analysis
of the DVP signal contour can give a better estimate of blood
pressure than either one alone. Once calibrated with a conventional
blood pressure cuff, the pressure pulse contour in association with
a knowledge of pulse wave velocity can be used to follow actual
systolic and diastolic blood pressure readings. Without such
calibration it is only possible to track not changes in blood
pressure through observation of the mean volume pulse amplitude,
the augmentation index and reflected wave changes.
[0210] Once aortic pulse wave velocity has been determined, it is
possible to convert a temperature stabilized volume pulse contour
signal into an accurate pressure pulse contour for ongoing
monitoring of blood pressure using conventional techniques. While
pulse wave velocity is an accurate way of tracking mean arterial
blood pressure, it does not accurately correlate with pressures on
either side of the mean (i.e. the systolic or diastolic
pressures).
[0211] As previously discussed in relation to FIG. 15A, the mean
value of the DVP contour can be found by taking the area above the
diastolic amplitude, under the DVP contour from the beginning of
one beat to the beginning of the next and dividing it by the time
duration of the beat. To derive the value for systolic and
diastolic blood pressures through observation of the excursion of
the DVP signal from its mean, it is essential to understand the
relationship of arterial volume change to arterial pressure change.
It should be noted that the DVP signal cannot be used to determine
mean blood pressure directly, since the raw PPG signal is high pass
filtered before being amplified which removes the baseline
amplitude of the PPG signal. Thus, it is necessary to use a volume
independent measure of mean blood pressure, such as pulse wave
velocity to derive systolic and diastolic values.
[0212] The DVP contour has an amplitude differential between the
systolic and diastolic values (DVP.sub.diff) that varies in a
nonlinear way with the arterial pulse pressure (PP) (i.e. the
difference between arterial systolic and diastolic pressure). The
relationship between arterial pulse pressure (PP) and DVP.sub.diff
varies between users as well. The DVP contour has a significantly
different shape than the pressure pulse contour. The peaks of the
DVP signal are much less defined and this results in the DVP signal
having a different mean amplitude than the pulse pressure contour.
The difference in shape occurs because of the diffusion of light in
the finger as it travels from the light source, through tissue to
arterial elements and back to the photodetector. This diffusion
smooths the shape of the DVP signal relative to the pressure pulse
contour. In order to better relate the shape of the DVP signal to
the arterial pressure pulse contour, it is possible to synthesize a
pressure pulse contour (RADIAL.sub.synth) from the DVP signal,
through the use of a transfer function applied to the DVP signal,
as will be described.
[0213] It has been observed that the amplitude of the synthesized
radial pressure pulse contour (RADIAL.sub.synth) will vary with the
amplitude of the DVP signal in a nonlinear fashion. This is evident
from the equation which relates arterial pressure change to
fractional volume change: 2 P = K * C 2 * V V
[0214] where .DELTA.P is a change in pressure in mmHg, K is a
calibration constant, C is pulse wave velocity, and V is arterial
volume. The sensing of a blood volume using a PPG device involves
the scattering of light within the finger and makes it difficult to
rely on the formula above alone to derive arterial pulse pressure
(PP) from the DVP contour.
[0215] U.S. Pat. No. 5,265,011 to O'Rourke discloses one technique
of transforming a radial artery pressure pulse contour into an
aortic pressure pulse contour through use of time domain or
frequency domain techniques. A transfer function is derived through
examination of sample data obtained invasively from the aorta and
noninvasively from the radial artery. A similar approach is
utilized in "On-line Synthesis of the Human Ascending Aortic
Pressure Pulse From the Finger Pulse", Mastafa Karamanoglu et al.,
Hypertension, Vo. 30, No. 6 December 1997 pgs. 1416-1424. The
change in shape from the volume pulse contour as seen in a finger
to a pressure pulse contour seen in the radial artery can be
described by a transfer function calculated from data obtained from
a tonometric and PPG apparatus for a particular user.
[0216] The method of the present invention is to determine the
nonlinear relationship between a particular user's blood pressure
and their pulse wave velocity. This method accomplishes calibration
of this nonlinear relationship by observing the blood pressure and
aortic or digital pulse wave velocity together over a significant
range of values. Once a set of values representing the simultaneous
changes in blood pressure and pulse wave velocity is obtained, a
conventional polynomial best fit curve fitting algorithm can be
used to derive an equation that can be used later to predict blood
pressure from pulse wave velocity alone. As long as the aortic or
digital pulse wave velocity correlate (i.e. indices based on the
shape and timing of a reflected wave) varies closely with mean
blood pressure, the calibration curve will permit accurate
subsequent measurements using only readings of a user's pulse wave
velocity.
[0217] Specifically, the method of calibration involves
simultaneous collection of pulse wave velocity and blood pressure
samples over a period of time as blood pressure varies
significantly. The sample data from a PPG sensor 12 attached to a
finger and a tonometric apparatus applied to the radial artery can
be used to create a transfer function for the user. The calibration
curve, obtained from the polynomial curve fitting algorithm, can be
used without need for recalibration for a matter of months.
Recalibration is necessary only to account for aging effects on the
arterial system.
[0218] As shown in FIG. 15B, a continuous noninvasive blood
pressure monitor 8, such as the Colin model 7000 blood pressure
monitor (available from Colin Medical Instruments Corp. of Texas)
could be used alongside PPG sensor 12 of system 10 for calibration
purposes. The unit is a wrist worn device that initially calibrates
itself against a reading from an integral cuff blood pressure
device. Thereafter, readings from the arterial tonometer can be
used by system 10 to give accurate beat to beat readings of
absolute blood pressure. Specifically, the PPG signal detected by
PPG sensor 12 can be used in association with the blood pressure
and pressure pulse contour information from the Colin 7000 to
provide a user with various blood pressure measures.
[0219] Alternatively, it should be noted that digital pulse wave
velocity could be used in place of aortic pulse wave velocity.
Aortic pulse wave velocity is about one half that of digital pulse
wave velocity, and accordingly, since there is a linear
relationship between aortic and digital pulse wave velocity, the
calibration process will produce an analogous curve using digital
pulse wave velocity. Accordingly, it would be possible to implement
blood pressure monitor 8 by the finger cuff bladder 29 (FIG. 4) in
association with Penaz techniques as previously discussed to
achieve similar calibration. In this case, the digital arterial
pressure, not the radial arterial pressure would be the calibrating
parameter.
[0220] The rise and fall of blood pressure, on a beat to beat
basis, in association with respiration is the simplest way to
measure blood pressure and pulse wave velocity over a small range
of values. Raising an arm and rising from a sitting position are
ways to provoke larger changes in blood pressure at the wrist. In
this way, it is possible to simultaneously sample blood pressure
and pulse wave velocity enabling the derivation of the nonlinear
relationship between these parameters for a particular user. It
should also be noted that a generalized transfer function could
also be used without individual calibration. However, for better
accuracy, it is desirable to create individual transfer functions
through a sampling of each user's DVP signal and radial tonometric
signals.
[0221] The calibration procedure described above will provide a
relationship curve that describes the nonlinear relationship
between a user's (either aortic or digital) pulse wave velocity and
blood pressure. It should be understood that any index that varies
closely with aortic or digital pulse wave velocity can be used to
derive a nonlinear relationship between the index and blood
pressure. Most of the indices discussed above (e.g.
.DELTA.T.sub.Ref, INDEX.sub.Ref, and INDEX.sub.2nd Deriv) can be
used for this purpose. Previous methods such as that disclosed in
U.S. Pat. No. 5,265,011 to O'Rourke and U.S. Pat. No. 5,882,311 to
O'Rourke both disclose the conversion of a digital pressure pulse
contour into an aortic pulse pressure contour using a transfer
function which is derived on the basis of blood pressure pulses
obtained from remote sites. The amplification and phase differences
between the two pressure pulse contours are measured by appropriate
signal analysis and processing techniques. In such a method the
transfer function is developed on the basis of remotely measured
blood pressure pulses and aortic blood pressure. In contrast, the
present invention discloses the development of a calibration curve
between blood pressure volume indices and aortic blood
pressure.
[0222] FIGS. 15C and 15D together show the steps taken to determine
the systolic blood pressure (BP.sub.sys) and the diastolic blood
pressure (BP.sub.dias) of a user according to the calibration
method 250 and the blood pressure determination method 260 of the
present invention.
[0223] Referring first to FIG. 15C, the calibration method 250
consists of the derivation of a number of transfer functions using
a commercial continuous non-invasive blood pressure monitor 8 (FIG.
15B) such as the Colin 7000 that generates a radial pressure pulse
contour on a beat to beat basis. Alternatively, the integrated
bladder and servo controller pressure device 29 discussed in
association with FIG. 4 could be used for an analogous purpose. By
continuously measuring the blood pressure of a user as discussed
above, it is possible to obtain a number of transfer functions (or
calibration curves) for a user between various cardiovascular
measures, as will be described.
[0224] Specifically, a transfer function TF.sub.1 is derived (251)
which converts a user's DVP contour to a synthesized radial pulse
contour RADIAL.sub.synth by monitoring the relationship between a
user's DVP signal and a user's pressure pulse contour. The transfer
function TF.sub.1 is derived using a commercial continuous
non-invasive blood pressure monitor 8 to generate a radial pressure
pulse contour on a beat to beat basis. As discussed above the
integrated bladder and servo controller pressure device 29 could be
used in the alternative.
[0225] Next, a transfer function TF.sub.2 is derived (252) which
converts a measure of pulse wave velocity (e.g. aortic or digital)
or a correlate of aortic pulse wave velocity such as INDEX.sub.Ref,
INDEX.sub.2nd Deriv, or .DELTA.T.sub.Ref to the user's mean
arterial blood pressure. The transfer function TF.sub.2 is derived
using blood pressure monitor 8 and the PPG sensor 12 and CPU 5 of
processing device 14 while having the user perform actions that
result in significant swings in mean blood pressure. The values for
mean blood pressure and pulse width velocity are correlated by
using a polynomial best fit curve algorithm.
[0226] Finally, a transfer function TF.sub.3 is derived (254) that
relates the systolic to diastolic excursion of the DVP signal to a
user's radial arterial pulse pressure. Again, transfer function
TF.sub.3 is obtained using blood pressure monitor 8 in conjunction
with PPG sensor 12 and CPU 5 of processing device 14. Values for
the systolic to diastolic excursion of the DVP signal are plotted
against corresponding radial arterial pulse pressure values. The
values are correlated by using a polynomial best fit curve
algorithm.
[0227] Once the calibration method 250 has been performed and the
transfer functions TF.sub.1, TF.sub.2, and TF.sub.3 are stored by
CPU 5 of processing device 14, the user may then proceed to use
system 10 independently of blood pressure monitoring device. Each
time the user requests information concerning blood pressure
measures, system 10 will execute a routine which applies blood
pressure determination method 260.
[0228] FIG. 15D shows the process steps of blood pressure
determination method 260. First, a user's DVP signal is obtained
(261) as has been previously discussed. Then the synthesized radial
pulse contour (RADIAL.sub.synth) is calculated (262) from the
user's DVP signal using transfer function TF.sub.1 which was
obtained as described above. Then the mean amplitude of the
synthesized radial pulse contour (RADIAL.sub.synth) is determined
(264) by taking the area under the synthesized radial pulse
(RADIAL.sub.synth) from the upstroke of one beat to the next and
dividing this by the duration of the beat. Also, the pulse pressure
(PP) or systolic to diastolic excursion of the synthesized radial
pulse contour (RADIAL.sub.synth) (i.e. the difference between the
systolic and diastolic amplitudes of (RADIAL.sub.synth)) is
calculated (266).
[0229] The mean amplitude of the synthesized radial pulse
(RADIAL.sub.synth) is divided by this systolic to diastolic
excursion (268). This expresses the mean amplitude as a fraction of
the amplitude differential (MEAN AMP.sub.Frac). For example, in the
case where mean pressure is 100 mmHg, the systolic pressure is 140
mmHg and the diastolic pressure is 80 mmHg. The pulse pressure (PP)
would then be equal to 140 mmHg-80 mmHg or 60 mmHg. Mean pressure
lies 20 mmHg above the diastolic pressure and is 20/60 or 1/3 of
the pulse pressure (PP).
[0230] Next, the systolic to diastolic amplitude differential of
synthesized radial pulse contour (RADIAL.sub.synth) in volts is
converted to a pulse pressure (PP) in mmHg (270) through the use of
transfer function TF.sub.3. That is, the amplitude of the pulse
pressure (PP) of the synthesized radial pulse (RADIAL.sub.synth)
measured in volts is converted to a pulse pressure (PP) in mmHg.
The derived function relates the systolic to diastolic excursion of
the DVP contour to that (i.e. the pulse pressure (PP)) of the
radial artery.
[0231] Mean arterial blood pressure MEAN.sub.ABP is then calculated
from either digital or aortic pulse wave velocity (or a pulse wave
velocity correlate) (272) using transfer function TF.sub.2. It
should be noted that mean arterial blood pressure MEAN.sub.ABP
could be obtained using such a transfer function applied to any
correlates of aortic pulse wave velocity such as INDEX.sub.REF,
INDEX.sub.2nd Derriv, or .DELTA.T.sub.REF (as discussed above).
[0232] Utilizing these three different transfer functions TF.sub.1,
TF.sub.2, and TF.sub.3, it is possible for system 10 to provide a
relatively accurate estimation of these various blood pressure
measures. Systolic blood pressure (BP.sub.sys) can be calculated
(274) according to the relation:
BP.sub.sys=MEAN.sub.ABP+PP(1-(MEAN AMP.sub.Frac))
[0233] Diastolic blood pressure (BP.sub.Dias) is then calculated by
subtracting the calculated pulse pressure (PP) from systolic blood
pressure (BP.sub.sys) (276).
[0234] As mentioned above, it is contemplated that system 10 can be
calibrated with a sophisticated noninvasive blood pressure monitor
such as the Colin 7000. It is anticipated that users would perform
the calibration at a point of purchase location (i.e. similar to
cell phone setup at a dealer before the cell phone can be used).
The alternative, discussed above would be to integrate system 10
with an inflatable cuff 29 so that blood pressure can be measured
continuously allowing for a separate calibration unit and allowing
for frequent calibration during the use of system 10.
[0235] It is also possible for users to follow trends (or changes)
in blood pressure through the examination of the pulse wave
velocity alone without calibration. This would provide a user with
a general sense of their blood pressure and information on blood
pressure changes could be used within a biofeedback model to assist
user's lower their blood pressure levels. The indices described
above, namely .DELTA.T.sub.Ref, INDEX.sub.Ref, and INDEX.sub.2nd
Deriv can also be generated directly from the DVP signal and used
as general indicators for cardiovascular health on their own.
[0236] The aortic pressure pulse contour provides valuable
information about the pressures the heart is pumping against.
Typically there is a substantial discrepancy between the pressure
profile measured with a blood cuff on the arm and the aortic
pressure profile. The pressure pulse contour, once calibrated
against an arm blood pressure reading taken simultaneously, can be
used to determine systolic and diastolic pressures thereafter.
Having a peripheral pressure pulse contour synthesized from the
volume pulse contour permits the synthesis of the aortic pressure
pulse contour. A generalized transfer function can be created to
derive the aortic pressure pulse contour as demonstrated by the
authors of the article "Functional Origin of Reflected Pressure
Waves in a Multibranched Model of the Human Arterial System",
Mustafa Karamanoglu et al., The American Physiological Society
(1994) H1681 to H1688.
[0237] It is also possible to estimate the respiratory contour
using the DVP signal and it characteristics. Specifically,
INDEX.sub.Ref (DVP augmentation index), .DELTA.T.sub.REF,
INDEX.sub.2nd derriv, mean DVP amplitude and other cardiovascular
indices vary with beat to beat changes in aortic pulse wave
velocity. This is due to changes in blood pressure associated with
respiration. It is known that during respiration, there are
synchronous periodic fluctuations of the volume of blood in all
body compartments, primarily on account of mechanical pressure and
pumping action.
[0238] Changes in pulse wave velocity are highly correlated with
obstructed respiratory effects, such as those apparent with sleep
apnea. With each inspiration, mean blood pressure falls. Thus, by
following mean blood pressure, it is possible to obtain the
respiratory rate and depth of respiration. Pulse wave velocity
(both digital and aortic), INDEX.sub.Ref, adaptively filtered
reflected wave timing and amplitude, INDEX.sub.2nd Deriv,
.DELTA.T.sub.Ref and mean blood pressure derived from the area
under the DVP signal can all be used to follow mean blood pressure
and thus to synthesize respiratory rate and the depth of
respiration.
[0239] As shown in FIGS. 16A, 16B, 16C and 16D a respiratory
contour, RESP, can be synthesized by observing the beat to beat
changes in pulse wave velocity and low pass filtering the signal
derived from each of the indices. Specifically, in FIG. 16A CPU 5
of processing device 14 performs the calculation (281) of a
particular physiological indicia, such as INDEX.sub.2nd Deriv over
the course of a number of DVP beats BEAT.sub.1, . . . BEAT.sub.N.
Then, the amplitude of the indicia is plotted over time (282).
Using a conventionally known polynomial curve fitting algorithm, it
is possible to interpolate between data points (284) and to produce
an approximately fitted curve for the respiratory contour RESP as
shown in FIG. 16D. Finally, the respiratory contour RESP is low
pass filtered (286) at a corner frequency of approximately 0.5
Hertz to remove spurious noise from the signal.
[0240] The depth of the fall in blood pressure with inspiration can
be used to monitor for respiratory obstruction, since the
inspiratory effort will increase with obstruction, resulting in a
greater inspiratory fall in blood pressure. Sleep apnea is a
condition affecting many people and its diagnosis is difficult,
requiring analysis of breathing patterns during sleep in a sleep
laboratory. By programming system 10 to monitor the augmentation
index, or another blood pressure indicator, it is possible to
determine if a person is at risk for sleep apnea and to follow
treatment effects. For example, a glove worn PPG sensor 12
communicating with processing device 14 provides this functionality
to users (not shown).
[0241] Further, the autonomic nervous system influences the PPG
signal and can provide information about the health of a user
autonomic nervous system. Very low frequency changes in the
nonpulsatile and pulsatile portions of the PPG signal can be
detected through spectral analysis techniques. These low frequency
changes are associated with autonomic nervous system influences and
can provide information about the health of the autonomic nervous
system.
[0242] As discussed, pulse wave velocity varies with blood pressure
and can be used as a correlate to track mean blood pressure.
Because blood pressure is under the control of the autonomic
nervous system, subtle changes in autonomic function can be
discerned by tracking blood pressure changes during particular
types of physical movement. For example, those individuals with a
family history of diabetes but who have not exhibited any clinical
changes in blood sugar will exhibit abnormalities indicative of
diabetic autonomic neuropathy. Examining pulse wave velocity when
the user stands up can reveals these autonomic changes. An
unaffected person will have little change in pulse wave velocity
while an affected person will show a significant drop in pulse wave
velocity, associated with a drop in blood pressure, on standing
up.
[0243] Aortic compliance is a powerful indicator of cardiovascular
health and cardiovascular risk. As discussed previously, many
authorities have observed that aortic compliance and carotid artery
compliance is closely related to age and that vascular compliance
is more closely related to physiological age than other measures
such as skin inelasticity, greying of hair, baldness, etc. There is
also evidence that aortic compliance is related to hypertension,
cardiac function, and left ventricular hypertrophy and can be
increased by exercise, hormonal therapy, antioxidant and
antihypertensive treatment. It has been proposed that deviation of
aortic compliance from the age-predicted norm may prove to be a
good predictor of cardiovascular pathology ("Vascular Compliance as
a Measure of Biological Age", Christopher J. Bulpitt et al., JAGS
June 1999--Vol. 47, No. 6 pgs. 657-663). Also, aortic compliance
was found to be significantly reduced in patients with stoke
compared with non-stroke control subjects ("Aortic Distensibility
in Patients with Cerebrovascular Disease", E. D. Lehmann et al.,
Clinical Science (1995) 89, pgs. 247-253).
[0244] Pulse wave velocity is an indirect measure of aortic
compliance. In fact, studies have shown that aortic pulse wave
velocity is strongly associated with the presence and extent of
atherosclerosis and constitutes a forceful marker and predictor of
cardiovascular risk in hypertensive patients ("Aortic Pulse Wave
Velocity as a Marker of Cardiovascular Risk in Hypertensive
Patients", Jacques Blacher, et al., Hypertension, May 1999, pgs.
1111-1117). Through the use of correlates of aortic pulse wave
velocity discussed above, system 10 can provide an accurate
assessment of cardiovascular risk for a user quickly and
easily.
[0245] As previously discussed, PPG sensor 12 can utilize one or
two LED's. While the PPG sensor 12 of the preferred embodiment of
the invention includes two LED's it is possible to conduct the
above noted analysis and obtain the above noted cardiovascular
indices using just a single LED. However, it is only possible to
obtain the measurement of blood oxygen saturation using a red
LED.sub.1 and an infrared LED.sub.2 as will be discussed.
[0246] Blood oxygen saturation is a physiological parameter of
critical importance in many medical conditions. The non-invasive
measurement of arterial oxygen saturation using PPG sensors known
as pulse oximetry is well established in clinical use. The
technique relies on the knowledge that haemoglobin and oxygenated
haemoglobin absorb incident light to varying degrees as a function
of wavelength.
[0247] In particular, at 658 nanometres (which corresponds to red
light), the absorption coefficient for haemoglobin is ten times
higher than that for oxyhemoglobin. At 880 nanometres (which
corresponds to infrared light), there is a much smaller difference
between the absorption coefficients between the two wavelengths. It
is thus possible to derive the proportion of oxyhemoglobin and
therefore the arterial oxygen saturation from a knowledge of the
absorption characteristics of the arterial blood at these two
wavelengths. That is, differential absorption of oxyhemoglobin and
deoxyhaemoglobin at these two wavelengths allows the relative
proportion of each to be determined as is well known to those
skilled in the art of biomedical engineering.
[0248] Alternatively, it would be possible to use two infrared LEDs
which are close to the isobestic point of haemoglobin (i.e.
approximately 880 nanometres). The isobestic point of haemoglobin
is defined as being the wavelength at which the haemoglobin is
relatively insensitive to the oxygenated status of the haemoglobin
molecule. Light emitting at 880 nanometres is close to the point
where the absorption of light by haemoglobin is not affected by the
oxygenation status of the haemoglobin molecule.
[0249] Further, by using PPG sensor 12 with two LEDs, an accurate
measure of digital pulse wave velocity can be made as the pulse
wave travels between the two LED's. Conventional methods for
measuring pulse wave velocity have utilized a between-LED spacing
of at least 3 centimeters, such as in U.S. Pat. No. 5,309,916 to
Hatschek. The most common way of measuring pulse wave velocity from
PPG signals is to measure the time from the "foot" of one signal
pulse to the "foot" of the other signal pulse. The "foot" of the
signal is relatively free from distortions introduced by local
reflection phenomena. The rest of the pulse contour is distorted
slightly because of local reflection effects.
[0250] It has been observed that for signals originating from light
sources 1 centimeter apart, the time delay of the DVP contour will
be approximately 1 millisecond. In order to sample this interval
with 1:1000 accuracy, it is necessary to sample the volume pulse
contour at a frequency of 1 megahertz. Currently, this sampling
speed can only be obtained with specialized data acquisition boards
and accordingly, is not particularly suitable for conventional
personal computing means.
[0251] The present invention can provide accurate DVP waveform
analysis at sampling rates as low as 200 hertz (although a sampling
rate of 1 kilohertz is preferable) has been found to provide
sufficient through the use of cross correlation (CC) analysis.
Processing device 14 determines the time delay between the volume
pulse contour as it passes between the two LEDs of PPG sensor 12
using CC analysis. CC provides information on the degree of
correlation between two signals according to the well known formula
of CC: 3 C C ( ) = + .infin. V 1 ( t ) V 2 ( t - ) t
[0252] CC is a function of the parameter .sup..tau., the lag
between V.sub.1 and V.sub.2. This CC relation can be used by
processing device 14 to calculate time delay from which pulse wave
velocity can be estimated. Cross correlation of two PPG signals has
traditionally resulted in several inaccuracies due to local
reflection effects. It has been determined that by filtering out
those parts of the volume pulse contour signal that are associated
with reflection effects, it is possible to appreciably decrease
reflection effects. Specifically, by high pass filtering the volume
pulse contour (e.g. above 8 Hertz and preferably above 10 Hertz)
prior to cross correlation, it has been observed that the
corrupting effects of reflection effects on the volume pulse
contour signal can almost be completely eliminated.
[0253] Another method of reducing reflection effects is to use an
adaptive predictor which requires the use of complex algorithms.
This method requires significant calculation on a real time basis
and takes a large number of samples before making an accurate
result. A third method which has been suggested is to band pass
filter the volume pulse contour signal at 12 hertz and to transform
the wave harmonic component at this frequency from real to complex
to allow for accurate and rapid estimation of phase delay which is
independent of sampling frequency.
[0254] Referring to FIGS. 1 and 16, once processing device 14 has
calculated and digitized the physiological signals, it is a simple
matter to convey that data to Web server 16 over communication
network 18 as part of an interactive diagnostic Web site system
300. The internet Web site hosted at Web server 16 would provide
service to users in possession of PPG sensor 12 appropriately
integrated with their processing device 14, as well as attract
visitors to the Web site through the display and description of
physiological signals. Finally, the Web site would allow
researchers to have access to physiological signals derived from
PPG sensors 12.
[0255] Preferably the communication protocol used with the
invention would be TCP/IP. Those skilled in the art will understand
the manner in which the data is formatted by processing device 14
prior to being transmitted over communication network 18 to Web
server 16. TCP/IP then parses the data into packets, each packet
including a field indicating the destination Web site 16.
Processing device 14 then outputs the packets onto communication
network 18. At minimum, the packets will contain data relating to
the identity of the user and an indication of the type of
measurement data being is encoded within the data message.
Optionally, other types of information could be provided such as
the time and date of the measurement and the type of medical device
which took the measurement.
[0256] The Web site hosted on Web server 16 would provide users
with additional functionality for analysis, storage, and retrieval
of physiological signals that they convey to the Web site. All
communication of physiological data would be encrypted in a secure
fashion to preserve privacy (350). The user would have the ability
to store their physiological data (352) as well as text based data
(354) in a personal database with access to the user in a password
protected secure fashion. The medical data file maintained for the
user at the Web site may be periodically updated to reflect
received measurement data. Specifically, the ability of system 10
described above to recognize each individual user through the
unique nature of their volume pulse contour adds an additional
level of security to system 10 by establishing a database of
physiological fingerprints.
[0257] Users would also be encouraged to store documentary
information describing their personal health at the Web site. This
would comprise a history of any medical problems they had
experienced and any medications they might be taking. Other
documentation describing the user, such as age, place of residence,
place of birth, occupation and other demographic data would be
sought. A family history of illness would be requested. Easy to use
on-line forms would be available at the Web site to assist users in
providing documentation.
[0258] The Web site hosted on Web server 16 could provide more
sophisticated analysis means then would be possible at the user's
processing device 14. The data stored by the user at the Web site
on Web server 16 would be accessible to the user and health
professionals authorized by the user anywhere any time. This would
facilitate the exchange of medical information. Users without
processing device 14 could use the database at the Web site for
secure storage and retrieval of their medical documentary
information.
[0259] Information stored by users in the database could be made
available (as long as authorized by the user) to researchers
interested in the relationship between users' physiological signals
and the accompanying documentation in the form of a research
database (362). Analysis of the physiological and documentary
information (364) from a sample of numerous users (e.g. several
thousand) would be helpful in developing a medical discipline
focused on the diagnosis and management of health issues through
examination of physiological signals derived from a PPG sensor 12
by the research community (365).
[0260] The Web site hosted on Web server 16 could also offer third
parties with educational resources (356), downloads (358) and
hyperlinks to other related Web site (360). Users of system 10
could also benefit from biofeedback for relaxation and blood
pressure reduction. Also, system 10 could be used to provide an
index of cardiovascular risk for users seeking insurance. System 10
could also indicate an user's emotional state for purposes such as
in the gaming field or as a lie detector. It could also permit
access to user's medical history in emergency situations using a
particular PIN or access code worn by the user.
[0261] FIG. 17 shows a contemplated biometric security system 400
according to the present invention. During the course of clinical
testing of a significant number of patients, it was observed that
the aortic reflected wave contour associated with a particular user
is unique to that user. Specifically, the changes in the DVP signal
which permits its use as a security feature are primarily related
to changes in the shape and timing of the reflected wave over a
period of months to years that produce a slowly changing unique
shape to every user's DVP signal.
[0262] Biometric security system 400 uses the various techniques
discussed above in respect of system 10 to isolate the aortic
reflected wave from a PPG signal for a user 402. It is contemplated
that other conventionally known techniques such as time frequency
analysis could be used to characterize the aortic reflected wave
from the DVP signal for pattern recognition and other security
purposes.
[0263] Specifically, biometric security system 400 utilizes PPG
sensor 12 and processing device 14 to obtain a user's reflected
wave profile. Biometric security system 400 then uses an access
controller 404 to store the user's biometric data in a biometric
database 406. Access controller 404 only allows authorized person
access to restricted resources 408 (e.g. bank accounts, buildings
etc.) if the authorized person's aortic reflected wave profile
matches one of the appropriate stored aortic reflected wave
profiles stored in biometric database 406 (i.e. the aortic
reflected wave profiles of authorized third parties can be stored
in biometric database 406 as well).
[0264] In this way, only authorized persons would only be allowed
access to resources, locations, on the basis of their particular
aortic reflected wave characteristics. It is contemplated that an
appropriately designed matching program would be used to compare
stored aortic reflected wave profile with an aortic reflected wave
that is extracted from a PPG signal obtained from the user using
the PPG sensor 12 of system 10 described above. It should be noted
that such a security system would have to periodically update the
store aortic reflected wave profiles (e.g. every 6 months), as the
aortic reflected wave profile of a user will change significantly
with age.
[0265] Finally, FIG. 18 is a sample screen capture from system 10
which provides the user with graphical information as to their own
DVP waveform (500), their heartbeat (502) and their respiration
contour (504).
[0266] While preferred embodiments of the invention have been
described, it will be appreciated that various changes can be made
within the scope of the appended claims.
* * * * *