(12) United States Patent
`Goodman
`
`(10) Patent N0.:
`(45) Date of Patent:
`
`US 6,616,613 B1
`Sep. 9, 2003
`
`US006616613B1
`
`(54) PHYSIOLOGICAL SIGNAL MONITORING
`SYSTEM
`
`(75) Inventor: Jesse B. Goodman, Mississauga (CA)
`(73) Assignee: Vitalsines International, Inc.,
`Mississauga (CA)
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 0 days.
`
`( * ) Notice:
`
`(21) Appl. No.: 09/559,424
`(22) Filed:
`Apr. 27, 2000
`
`(51) Int. Cl.7 ................................................ .. A61B 5/02
`(52) US. Cl. ...................... .. 600/504; 600/500; 600/300
`(58) Field of Search ............................... .. 600/300—301,
`600/323, 500, 504, 507; 128/905, 920—925;
`713/186
`
`(56)
`
`References Cited
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`
`(List continued on next page.)
`
`Primary Examiner—Robert L. Nasser
`Assistant Examiner—Patricia Mallari
`(74) Attorney, Agent, or Firm—Bereskin & Parr
`(57)
`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 sen
`sor 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 re?ected Wave pulse present Within the digital
`volume pulse derived from the PPG pulse contour. Signal
`characteristics of the systolic re?ected Wave pulse can be
`determined through various pulse analysis techniques
`including derivative analysis of the digital volume pulse
`signal, bandpass ?ltering or respiratory matrix frequency
`extraction techniques. By subtracting the systolic re?ected
`Wave pulse contour from the digital volume pulse contour,
`characteristics of the systolic Wave pulse can also be iden
`ti?ed. The system also provides for the accurate determina
`tion of systolic and diastolic blood pressure by using a
`non-invasive blood pressure monitor to calibrate the rela
`tionships 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 trans
`mittal of such data to the system Web site for further
`analysis, storage, and retrieval purposes.
`
`39 Claims, 25 Drawing Sheets
`
`PPG SENSOR E]
`
`13:
`
`12
`
`COMMUNICATION
`NETWORK
`
`WEB
`SERVER
`
`16)
`
`FITBIT EXHIBIT 1007
`
`Page 1 of 48
`
`

`
`US 6,616,613 B1
`Page 2
`
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`“AC Instrumentation Ampli?er for Bioimpedance Measure
`ments” Ramon Pallas—Areny et al. Communications vol. 40,
`No. 8: 830—833 Aug. 1993.
`“Age—Related Abnormalities in Arterial Compliance Iden
`ti?ed by Pressure Pulse Contour Analysis” Gary E. McVeigh
`et al. Hypertension vol. 33: 1392—1398, 1999.
`“An Integrated Blood Volume Pulse Biofeedback System for
`Migraine Treatment” Kenneth L. Lichstein et al. Biofeed
`back and Self—Regulation, vol. 8, No. 1: 127—134 1983.
`
`“An Ultra—High Common—Mode Rejection Ratio (CMRR)
`AC Instrumentation Ampli?er for Laplacian Electrocardio
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`“Aortic Compliance in Human Hypertension” Zhaorong Liu
`et al. Hypertension vol. 14; 129—136, 1989.
`“Aortic Distensibility in Patients With Cerebrovascular Dis
`ease” E.D. Lehmann et al. Clinical Science vol. 89:
`247—253, 1995.
`“Aortic Pulse Wave Velocity as a Marker of Cardiovascular
`Risk in Hypertensive Patients” Jacques Blacher, et al.
`Hypertension vol. 33: 1111—1117, 1999.
`“Arterial compliance increases after moderate—intensity
`cycling” BronWyn A. KingWell et al. American Journal of
`Physiology vol. 273: 2186—2191, 1997.
`“Artifact reduction in photoplethysmography” MattheW J.
`Hayes et al. Applied Optics vol. 37, No. 31: 7437—7446,
`Nov. 1998.
`“Assessment of Vasoactive Agents and Vascular Aging by
`the Second Derivative of Photoplethysmogram Waveform”
`Kenji TakaZaWa et al. Hypertension vol. 32: 365—370, 1998.
`“Autonomic control of skin microvessels: assessment by
`poWer spectrum of photoplethysmographic Waves” Luciano
`Bernardi et al. Clinical Science vol. 90: 345—355, 1996.
`“Blood Pressure Control: A Comparison of Feedback and
`Instructions Using Pulse Wave Velocity Measurements”
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`humans” Gérard M. London et al, Hypertension vol. 10:
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`tion—Effects of Re?exes in the Arterial Tree” Morten Ben
`thin et al. Ultrasound in Medicine & Biology vol. 17, No. 5:
`461—469, 1991.
`“Comparison of Biofeedback Pulse Wave Velocity and Pro
`gressive Relaxation in Essential Hypertensives” Peter Walsh
`et al. Perceptual and Motor Skills vol. 44, 839—843, 1977.
`“Computation of Aortic Pulse Wave Velocity and Aortic
`Extensibility from Pressure Gradient Measurements” Alain
`C. Lapointe et al. Canadian Journal of Physiology Phar
`macology vol. 53: 940—946, 1975.
`“Continuous assessment of hemodynamic control by com
`plex demodulation of cardiovascular variability” Junichiro
`Hayano et al. American Journal of Physiology vol. 33:
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`“Differential effects of Wave re?ections a peripheral resis
`tance on aortic blood pressure: a model—based study” David
`S. Berger et al. American Journal of Physiology vol. 266:
`1626—1642, 1994.
`“Early autonomic dysfunction in patients With diabetes
`mellitus assessed by spectral analysis of heart rate and blood
`pressure variability” K. Laederach—Hofmann et al, Clinical
`Physiology vol. 19, No. 2: 97—106, 1999.
`“Elastic Properties and Windkessel Function of the Human
`Aorta” Gustav G. BelZ Cardiovasc Drugs T her vol. 9:
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`“Estimation of Central Aortic Pressure Waveform by Math
`ematical Transformation of Radial Tonometry Pressure”
`Chen—Huan Chen et al. Circulation vol. 95: 1827—1837,
`1997.
`“Exponentially Tapered T—tube Model in the Characteriza
`tion of Arterial Non—uniformity” Kuo—Chu Chang et al. J.
`Theor Biology vol. 183: 35—46, 1996.
`
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`

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`US 6,616,613 B1
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`“Functional origin of re?ected pressure Waves in a rnulti
`branched model of the human arterial systern” Mustafa
`Kararnanoglu et al. American Journal of Physiology vol.
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`rnann. M.D. American Heart Journal vol. 99, No. 4:
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`“Haernodynarnic basis for the development of left ventricu
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`“In?uence of aortic Cornpliance on Coronary Blood FloW”
`Francis L. Abel Circulatory Shock vol. 12: 265—276, 1984.
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`“Manipulation of Ascending Aortic Pressure and FloW Wave
`Re?ections With the Valsalva Maneuver: Relationship to
`Input Impedance” Joseph P. Murgo et al. Circulation vol. 63,
`No. 1: 122—132, 1981.
`“Measurement of Heart Rate Variability: A Clinical Tool or
`a Research Toy?” Heikki V. Huikuri et al. Journal of the
`American College of Cardiology vol. 34, No. 7: 1878—1883,
`1999.
`“Measurement of Pulse—Wave Velocity Using a Beat—Sarn
`pling Technique” J.D. Pruett et al. Annals of Biomedical
`Engineering vol. 16: 341—347, 1988.
`“Monitoring of heart and respiratory rates by photoplethys
`rnography using a digital ?ltering technique” K. Nakajirna et
`al. Med. Eng. Phys. vol. 18: 365—372, Jul. 1996.
`“Monitoring of respiratory and heart rates using a ?bre—op
`tic sensor” L.G. Lindberg et al. Medical & Biological
`Engineering & Computing vol. 30: 533—537, 1992.
`“Nonhurnan prirnate model for regional Wave travel and
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`80: 1652—1659, 1989.
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`tion: repeatability interrelationshis and trial sample size”
`Yu—Lu Liang et al. ClinicalScience vol. 95: 669—679, 1998.
`“Noninvasive Pulse OXirnetry UtiliZing Skin Re?ectance
`Photoplethysrnography” YitZhak Mendelson et al. IEEE
`Transactions of Biomedical Engineering vol. 35, No. 10:
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`“On—line Synthesis of the Human Ascending Aortic Pressure
`Pulse from the Finger Pulse” Mustafa Kararnanoglu et al.
`Hypertension vol. 30, No. 6: 1416—1424, 1997.
`“Photo—Electric Plethysrnography as a Monitoring Device
`in Anaesthesia” J .C. Dorlas et al British Journal of Anaes
`thesiology vol. 57: 524—530, 1985.
`“Photoplethysrnographic Assessment of Pulse Wave Re?ec
`tion” Philip J. ChoWiencZyk et al. Journal of the American
`College of Cardiology vol. 34, No. 7: 2007—2014, 1999.
`“Pressure Wave propagation in a rnultibranched model of the
`human upper limb” Mustafa Kararnanoglu et al. American
`Journal ofPhysiology vol. 269: 1363—1369, 1995.
`“Pulsatile FloW and Pressure in Human Systernic Arteries”
`Michael F. O’Rourke et al. Circulation Research vol. 46:
`363—372, 1980.
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`tension vol. 14: 147—157, 1996.
`
`“Pulse Wave Analysis and Arterial Stiffness” Ian B. Wilkin
`son et al. Journal of Cardiovascular Pharmacology vol. 32:
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`“Re?ection in the systemic arterial system: effects of aortic
`and carotid occlusion” G.C. Van Den Bos et al. Cardiovas
`cular Research vol. 10: 565—573, 1976.
`“Regional Wave travel and re?ections along the human
`aorta: a study With siX sirnultaneous rnicrornanornetric pres
`sures” Ricky D. Latharn et al. Circulation vol. 72, No. 6:
`1257—1269, 1985.
`“Relaxation pretraining, pulse Wave velocity and thermal
`biofeedback in the treatment of essential hypertension”
`Carolyn Buby et al. International Journal of Psychophysi
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`vous systern activities in reference to heart rate variability”
`M. Okada et al. MedicalInformation vol. 21, No. 1: 81—90,
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`Feedback” AndreW Steptoe et al. Journal of Psychosomatic
`Research vol. 20: 417—424, 1976.
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`Arteries in Man ” R. Busse et al. P?uger Arch vol. 360:
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`to the Heart” Roberto Burattini, et al. Circulation Research
`vol. 68: 85—99, 1991.
`“Use of Pulse Transit Time as a Measure of Inspiratory
`Effort in Patients With Obstructive Sleep Apnoea” D.J.
`Pitson et al. vol. 8: 1669—1674, 1995.
`“Use of TWo OXirneters to Investigate a Method of Move
`rnent Artefact Rejection Using Photoplethysrnographic Sig
`nals” A.R. Visrarn British Journal of Anaesthesia vol. 72:
`388—392, 1994.
`“Value to Beat—to—Beat Blood Pressure Changes, Detected
`By Pulse Transit Time, in the Management of the Obstruc
`tive Sleep Apnoea/Hypopnoea Syndrorne” D.J.Pitson et al.
`vol. 12: 685—692, 1998.
`“Vascular Cornpliance as a Measure of Biological Age”
`Christopher J. Bulpitt et al. Journal of American Geriatric
`Society vol. 47: 657—663, 1999.
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`cations in Ventricular Function” Michael F. O’Rourke et al.
`Hypertension vol. 11: 327—337, 1993.
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`O’Rourke et al. Arch Intern Med vol. 144: 366—371, Feb.
`1984.
`C J Harland et al., “Electric potential probes—neW direc
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`
`Page 3 of 48
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`

`
`US 6,616,613 B1
`Page 4
`
`Boo—Ho Yang et al., “Sensor Fusion For Noninvasive Con
`tinuous Monitoring Of Pulsating Blood Pressure Based On
`An Arterial Hernodynarnic Model”, WWW.thoughttechnolo
`gy.corn/gsr.htrn
`WWWrjlsysterns.corn/research/ipgl.htrnl
`WWW.rnedis—de.corn/products.htrnl http://hrf.jsc.nasa.gov/
`cbpd.htrn.
`
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`ence Inc., London, United Kingdom and Lund, SWeden.
`
`* cited by eXarniner
`
`Page 4 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 1 0f25
`
`US 6,616,613 B1
`
`18
`
`14
`
`5
`
`COMMUNICATION
`NETWORK
`
`PPG SENSOR
`
`_7_
`
`k 13 =,
`12
`
`9
`
`11
`
`WEB
`SERVER
`
`16/
`
`FIG. 1
`
`Page 5 of 48
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`

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`U.S. Patent
`
`Sep. 9, 2003
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`Sheet 2 0f25
`
`US 6,616,613 B1
`
`To /
`PROCESSING
`DEVICE 14
`
`FIG. 2
`
`Page 6 of 48
`
`

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`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 3 of 25
`
`US 6,616,613 B1
`
`VI‘
`01
`
`Page 7 of 48
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`Page 7 of 48
`
`

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`U.S. Patent
`
`Sep. 9, 2003
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`Sheet 4 0f25
`
`US 6,616,613 B1
`
`4,2 ®
`
`46
`
`46
`
`12
`
`(
`
`29
`
`FIG. 4
`
`Page 8 of 48
`
`

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`U.S. Patent
`
`Sep. 9, 2003
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`Sheet 5 0f25
`
`US 6,616,613 B1
`
`18
`
`HARDWIRE
`
`COMMUNICATION
`NETWORK
`
`OR
`
`[14
`
`W
`RF
`0 c1 c1 [:1 D
`CONNECTION
`C1 C1 O D U
`DC]
`0
`
`12 :
`
`FIG. 5
`
`Page 9 of 48
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`

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`U.S. Patent
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`Sep. 9, 2003
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`Sheet 6 M25
`
`US 6,616,613 B1
`
`mi .GE
`
`HE .UE
`
`4 4. é 4
`
`
`
`52:00 mw_:n_ mSwwmE 622%
`
`
`
`
`
`4
`
`ON .GE
`
`mw .@E
`
`Page 10 of 48
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`

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`U.S. Patent
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`Sep. 9, 2003
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`Sheet 7 0f25
`
`US 6,616,613 B1
`
`A
`
`“E1
`D
`6
`>
`D
`o
`o
`CO
`
`A
`
`B
`
`D
`
`C
`
`E
`
`»
`TIME
`
`FIG. 8
`
`Page 11 of 48
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`

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`U.S. Patent
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`Sep. 9, 2003
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`Sheet 8 0f 25
`
`US 6,616,613 B1
`
`106
`
`Obtain Flaw PPG
`Signal from PD1 & PD2
`X 0 J;
`i
`Condition & Digitize
`Raw PPG Signal
`l
`Filter Out Non-Pulsatile
`& Slowly Pulsatile Components
`from Conditioned PPG Signal
`to Obtain DVP Signal
`+
`K--—1O8
`Temperature Correct
`DVP Signal
`K110
`+
`Conduct Pulse Contour
`Analysis of DVP Signal
`+
`K112
`Determine CV lndices
`& Respiratory Data
`K114
`+
`Store, Display to User &
`Transmit CV & Respiratory
`Data to Web User
`
`@
`
`FIG. 9A
`
`Page 12 of 48
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`

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`Sheet 9 0f25
`
`US 6,616,613 B1
`
`l/108
`116 @ K,
`
`Instruct User to Cool
`Finger on Ice Cube
`+
`K118
`instruct User to Position
`Finger on PPG Sensor
`of User Input Device
`K120
`+
`Determine Amplitude of Flaw PPG Signal
`& DVP Signal at Time T1 &T2,
`TN
`as the User's Finger Warms Up
`l
`#122
`Calculate the Change in Raw PPG Signal
`Bin Time Points T1,
`TN (APPG i) for
`i=1 to n-1 & the Change in DVP Signal
`Bin Time Points T1,
`TN (APPGi)
`for i=1 to n-1
`t
`Calculate K1 to Km a/c to the
`Relation Ki=APPGi for i=1 to n-1
`ADVPi
`F\126
`t
`Average All Ki’s to Obtain K
`i
`@
`
`F\124
`
`FIG. 9B
`
`Page 13 of 48
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`

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`U.S. Patent
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`Sep. 9, 2003
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`Sheet 10 0f 25
`
`US 6,616,613 B1
`
`DVP
`PULSE CONTOUR
`
`bl
`no
`
`Page 14 of 48
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`

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`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 11 0f25
`
`US 6,616,613 B1
`
`DVP PULSE CONTOUR
`
`f
`
`62:55
`A 66555
`
`FIRST DERIV
`
`A
`
`A
`
`FIG. 11A T"“
`
`A
`
`Time
`
`FOURTH DERIV
`
`FIG. 11B
`
`6 to 20 HZ FILTER
`
`FIG. 11D
`
`Page 15 of 48
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`

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`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 12 0f 25
`
`US 6,616,613 B1
`
`204
`K.’
`
`1/200
`@
`202
`K’
`High Pass Filtering
`DVP Signal
`l
`Smoothing
`DVP Signal
`206
`K,”
`i
`Sample M DVP
`Beats at N Times
`208
`1
`K...
`Synchronize M
`DVP Beats Using
`Identified Foot (at T1)
`of Each DVP Beat
`210
`K,’
`l
`Arrange Amplitude
`Data for M DVP Beats
`in Time Columns
`(SYNCT)
`212
`i
`K’
`interpolate Data
`Within Each Time
`Column (SYNCT)
`214
`i
`K,
`Band Pass Filter Data
`Within Each Time
`Column (SYNCT)
`
`@
`
`FIG. 12A
`
`Page 16 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 13 0f 25
`
`US 6,616,613 B1
`
`1/208
`@
`220 f’
`Calculate the First
`Derivative of DVP Beats
`Beat1 to BeatM
`222
`K’
`i
`Measure Slope of First
`10% of First Derivative
`& Extrapolate Back to
`Time Axis to Obtain Foot
`for Each DVP Beats
`Beat1 to BeatM
`224
`K.’
`i
`Measure Amplitude of
`M DVP Beats
`Beat1 to BeatM at T1
`226
`K”
`1;
`Normalize M DVP Beats
`0
`so that All DVP Beats =
`at T1 and Align All
`Beats at T1
`
`@
`
`FIG. 12B
`
`Page 17 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 14 6f 25
`
`US 6,616,613 B1
`
`A
`
`i
`=73 A13
`5 A12
`A11
`
`BEAT1
`
`ELG_-l2_C
`
`' . .
`
`> Time
`
`T1 T2 T3
`
`TN
`
`A
`
`j; A
`:5 23
`E
`< A22
`
`A21
`
`BEAT2
`
`FIG. 12D
`
`. ' .
`
`> Time
`
`T1 T2 T3
`
`TN
`
`A
`
`A
`CD 5 “"3
`%AM2
`
`<
`
`BEATM
`
`FIG. 12E
`
`AW
`
`' ' '
`
`Time
`
`TN
`
`Page 18 of 48
`
`

`
`U.S.
`Patent
`
`Sep. 9, 2003
`
`Sheet 15 0f 25
`
`US 6,616,613 B1
`
`T1
`
`0
`0
`
`O
`
`D
`O
`
`BEAT1
`BEATZ
`
`O
`
`O
`O
`
`T2
`
`A12
`A22
`
`' ° '
`
`0 Q 0
`
`BEATM
`
`AM2
`O
`+SYNC1 +SYNC1
`
`FIG. 12F
`
`Spreadsheet A
`
`TN
`
`A1N
`A2N
`
`O
`
`O
`.
`
`AMN
`+SYNC1
`
`5000-
`
`T
`T13 4 15
`
`T25
`
`T35
`
`T1 Of BIEIA-II-1 =1 T11
`(T i
`2:3, '
`
`T1 Of
`
`'
`Time (mSec)
`FIG. 12G
`
`T1 of
`
`'
`
`>
`
`5000-
`
`
`
`Amplitude (mV)
`
`T15
`
`, .->< ----- _ _
`
`SYNC5
`\[ T35
`
`__ .x ----- -.
`
`T25
`
`.
`
`'
`
`""""" - ->< --------- "
`
`L
`
`k
`
`>
`
`Time (mSec)
`FIG. 12H
`
`Page 19 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 16 0f 25
`
`US 6,616,613 B1
`
`FIG. 13
`
`Page 20 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 17 of 25
`
`US 6,616,613 B1
`
`’
`
`
`
`m>m>>o_..9o_o
`
`
`
` N./‘m>m>>nm..um_._wm_
`
`6.666.5E96:nugazebo50.3n6
`
`{N
`
`
`
`xm>m>>o__o..m>m
`
`
`
`
`
`:95:.6£n_wn_\<xmwm.6E96:uxmu:_m>=m>_.mn_ucoomm
`
`
`
`
`
`Page 21 of 48
`
`Page 21 of 48
`
`
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 18 of 25
`
`US 6,616,613 B1
`
`Derivation of Mean Volume Pulse Amplitude
`
`Mean Volume Pulse Amplitude =
`Area Under contour/Duration of DVP Pulse
`
`Peak of DVP Pulse
`\
`
`’\—s
`
`T: Duration of Pulse A
`
`FIG. 15A
`
`Page 22 of 48
`
`Page 22 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 19 of 25
`
`US 6,616,613 B1
`
`
`
`
`BLOODPRESSUREMONITOR
`
`PPGSENSOR
`
`Page 23 of 48
`
`COMMUNICATION
`
`NETWORK
`
`18
`
`WEB SERVER
`
`16
`
`FIG.15B
`
`Page 23 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 20 of 25
`
`US 6,616,613 B1
`
`/250
`
`251
`
`Derive TF1, which Relates
`DVP Contour to RADlALsynth
`
`
`
`
`
`
`
`
`
`Derive TF2 which Relates
`PWV (Aortic or Digital) or
`Correlate of Pulse Wave Velocity
`to Mean Arterial Blood Pressure
`(MEANABP)
`
`252
`
`254
`
`
`
`
`
`
`
`
`Derive TF3 which Relates the
`Systolic-Diastolic excursion of
`the DVP Signal in Volts to
`Radial Arterial Pulse Pressure
`(PP) in mmHg
`
`
`
`
`
`
`
`
`FIG. 15C
`
`Page 24 of 48
`
`Page 24 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 21 of 25
`
`US 6,616,613 B1
`
`‘/260
`
`® 261
`
`
`
`Calculate RADIALSW1 Curve
`from DVP Signal Using TF1
`
`
`
`Calculate Mean Amplitude
`of RAD|ALsynth Curve
`
`262
`
`264
`
`266
`
`
`
`
`
`
`
`
`268
`
`270
`
`274
`
`
`
`Calculate MEAN AMPFRAC
`Mean Amplitude of RADlALsynth
`
`= Systolic-Diastolic Excursion of RADlALSynth
`
`
`Convert PP of RAD|AL3ynth in
`Volts to PP in mmHg Using TF3
` 272
`
`Calculate MEANABP From PWV
`or PWV Correlate Using TF2
`
`
`BPSYS = MEANABP + PP(1- (MEAN AMPFRAC»
`
`
`
`
`
`BPDIAS = BPSYS - PP
`
`276
`
`FIG. 15D
`
`Page 25 of 48
`
`
`
`Calculate Pulse Pressure (PP)
`or Systolic-Diastolic Excursion
`of RADIALSW,
`
`Page 25 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 22 of 25
`
`US 6,616,613 B1
`
`Plot Amplitude Value of Indicia Over Time
`
`284
`
`(i.e. PWV,
`
`Calculate Indicia
`|NDEXRef |NDEX2nd Derjv...
`
`/280
`for BEAT1,...BEATn) 282
`
`
`Amplitude
`
`BEAT1
`
`BEAT2
`
`
`
`
`
`—————F|G'16B
`
`Time
`
`|NDEX2nd Deriv
`
`’‘ FIG. 16C
`
`Time
`
`
`Page 26 of 48
`
`Page 26 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 23 of 25
`
`US 6,616,613 B1
`
`RESEARCH COMMUNITY
`
`365
`
`1
`
`16
`
`
`
`INTERNET CONNECTION
`
`V|TALSINES.COM
`
`1
`
`WEBSITE
`
`
`
`
`
`Research Database
`
`
`
`Data transferred from each User's database to the
`research database only with express permission of each user.
`All data stripped of User's ID.
`
`
`
`_ 356
`
`DOWNLOADS
`
`E[)UCAT|QNA|_
`RESOURCES
`
`LINKS TO
`
`OTHER SITES
`
`
`
`
`
`358
`
`TEXT BASED DATA
`
`PHYSIOLOGICAL DATA
`
`USER'S PASSWORD
`
`
`
`
`
`ONLINEDATA
`
`ANALYSIS
`
`I /
`
`
`PROTECTED DATABASE
`
`ENCRYPTED & SECURE INTERNET CONNECTION
`
`PHYSIOLOGICAL &
`TEXT BASED DATA
`
`14
`
`USER'S PC
`
`FIG. 17
`
`Page 27 of 48
`
`Page 27 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 24 of 25
`
`US 6,616,613 B1
`
`400
`
`402
`
` BIOM ETRIC
`
`
`
`DATABASE
`
`
`
` ACCESS
`CONTROLLER
`
`
`
` RESTRICTED
`
`RESOURCE
`
`
`
`410
`
`FIG. 18
`
`Page 28 of 48
`
`Page 28 of 48
`
`

`
`U.S. Patent
`
`Sep. 9, 2003
`
`Sheet 25 of 25
`
`US 6,616,613 B1
`
`PULSE WAVEFORM
`
`0.300-
`
`0.200-
`
`0.100-
`
`0.000-
`
`-0.100-
`
`-0.200-
`
`
`
`—___
`jfl-I--.'Ajj.I
`k_I.‘—lITl‘-Lilith‘
`
`I!1‘_,I1!_§!1—-k‘_-
`
`111u—u1‘.'-n-
`
`
`
`
`
`
`HEARTBEAT
`
`
`
`I.&.I—l.I1.II—.I1,n1.n
`twp»mrprnmmpmlmg-1|Ilmpmlnrpaml
`mnmnummumnmimcuumunmimmnmu
`
`
`1'|.:|'|.1'|.--'|1'u—'u
`
`
`|j—-in
`
`
`
`
`
`FIG. 19
`
`Page 29 of 48
`
`Page 29 of 48
`
`

`
`US 6,616,613 B1
`
`1
`PHYSIOLOGICAL SIGNAL MONITORING
`SYSTEM
`
`FIELD OF THE INVENTION
`
`This invention relates to a physiological signal monitor-
`ing system and more particularly to a system which allows
`a user to determine various types of physiological informa-
`tion and which allows a user to electronically access this
`information over a communication network.
`
`BACKGROUND OF THE INVENTION
`
`Various types of instrumentation for monitoring physi-
`ological 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 physi-
`ological 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 recog-
`nized 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.
`
`In an attempt to provide consumers and health profes-
`sionals with non-invasive blood pressure measuring equip-
`ment for patient safety and convenience, photoplethysmo-
`graph (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 instanta-
`neously track arterial blood volume changes during the
`cardiac cycle and are used within physiological signs moni-
`toring devices.
`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.
`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.
`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.
`Also, there are measurement and instrumentation diffi-
`culties associated with PPG sensors such as the presence of
`
`10
`
`15
`
`20
`
`25
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`2
`
`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 accu-
`rately predict blood pressure characteristics using PPG read-
`ings alone.
`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
`
`travels
`upper limbs, has significantly greater amplitude,
`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.
`
`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 associ-
`ated 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 compli-
`ance (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.
`
`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
`
`Page 30 of 48
`
`Page 30 of 48
`
`

`
`US 6,616,613 B1
`
`3
`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.
`For example, U.S. Pat. No. 5,265,011 to O’Rourke dis-
`closes 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 dias-
`tolic 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 t