WO2014143962A4 - System and method for characterizing circulatory blood flow - Google Patents

System and method for characterizing circulatory blood flow Download PDF

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Publication number
WO2014143962A4
WO2014143962A4 PCT/US2014/028167 US2014028167W WO2014143962A4 WO 2014143962 A4 WO2014143962 A4 WO 2014143962A4 US 2014028167 W US2014028167 W US 2014028167W WO 2014143962 A4 WO2014143962 A4 WO 2014143962A4
Authority
WO
WIPO (PCT)
Prior art keywords
integer
heart rate
computing device
biological signal
blood volume
Prior art date
Application number
PCT/US2014/028167
Other languages
French (fr)
Other versions
WO2014143962A3 (en
WO2014143962A2 (en
Inventor
Jan K. Berkow
Anne M. Brumfield
Original Assignee
Intelomed, Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US13/839,534 external-priority patent/US9002440B2/en
Application filed by Intelomed, Inc filed Critical Intelomed, Inc
Priority to EP14762395.3A priority Critical patent/EP2967502A4/en
Priority to AU2014227994A priority patent/AU2014227994A1/en
Priority to CA2904682A priority patent/CA2904682A1/en
Publication of WO2014143962A2 publication Critical patent/WO2014143962A2/en
Publication of WO2014143962A3 publication Critical patent/WO2014143962A3/en
Publication of WO2014143962A4 publication Critical patent/WO2014143962A4/en

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026—Measuring blood flow
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4848—Monitoring or testing the effects of treatment, e.g. of medication
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4869—Determining body composition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4884—Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A computer-implemented method for characterizing circulatory blood volume and autoregulatory compensatory mechanisms to maintain circulatory blood volume is disclosed. A biological signal that emulates the arterial pulse wave is collected from a sensor. Three derived parameters are extrapolated from the biological signal. The first parameter, circulatory stress, reflects of the changes of the heart rate frequency. The second, circulatory blood volume, reflects the changes in the frequency strength of the heart rate frequency. The third, Pulse Volume Alteration (PVA) Index is a ratio of the sum of the strengths of the heart rate frequency harmonics to the strength of the heart rate frequency of the unprocessed biological signal. Each parameter is compared to a threshold value and assessed to determine an adequacy of circulatory blood volume and an appropriateness of the autoregulatory mechanisms used to maintain circulatory blood volume adequacy.

Claims

AMENDED CLAIMS received by the International Bureau on 12 March 2015 (12.03.2015) What is claimed is:
1. A method for characterizing a circulating blood volume, the method comprising: receiving, by a computing device, a biological signal emulating an arterial pulse wave from a sensor associated with a human body; calculating, by the computing device, a plurality of integer harmonics of a heart rate from the biological signal, wherein each of the plurality of integer harmonics is characterized by an integer harmonic amplitude; calculating from the plurality of integer harmonic amplitudes of the heart rate, by the computing device, at least one derived parameter in a frequency domain comprising a measure of total harmonic distortion; and characterizing the circulating blood volume by comparing, by the computing device, the at least one derived parameter to a baseline value.
2. The method of claim 1, wherein the sensor comprises one or more of the following: a transmissive photo-optic sensor; a reflective photo -optic sensor; a pressure transducer; a tonometry device; a strain gauge; an ultrasound device; an electrical impedance device; and a radar device.
3. The method of claim 1, further comprising: conditioning the biological signal to form a conditioned biological signal; and calculating, by the computing device, at least one second derived parameter in the frequency domain based on the conditioned biological signal.
4. The method of claim 3, wherein conditioning the biological signal comprises amplifying the biological signal or filtering the biological signal.
5. The method of claim 1, wherein calculating a plurality of integer harmonics of a heart rate from the biological signal comprises:
sampling, by the computing device, the biological signal into a plurality of discrete data within a time window, to form windowed discrete signal data; and
performing, by the computing device, a spectrum analysis of the windowed discrete signal data.
6. (Previously presented) The method of claim 5, wherein performing a spectrum analysis of the windowed signal data comprises applying a Fast-Fourier Transform to the windowed signal data.
7. The method of claim 5, wherein performing a spectrum analysis of the windowed signal data comprises applying a wavelet transformation to the windowed signal data.
8. The method of claim 1, further comprising comparing a pattern of the at least one derived parameter in the frequency domain over time to a library of patterns of the derived parameter in the frequency domain over time.
9. The method of claim 1, wherein calculating the measure of the total harmonic distortion comprises summing together the integer harmonic amplitude of each of the plurality of integer harmonics of the heart rate.
10. The method of claim 1, wherein calculating the measure of the total harmonic distortion comprises:
summing together the integer harmonic amplitude of each of the plurality of integer harmonics of the heart rate to yield a numerator, and
dividing the numerator by an amplitude of a fundamental frequency of the heart rate.
11. The method of claim 1 , wherein calculating the measure of the total harmonic distortion comprises:
setting a denominator equal to the integer harmonic amplitude of an integer harmonic having a largest integer harmonic amplitude value among the plurality of integer harmonics of the heart rate;
taking a square root of a sum of squares of the integer harmonic amplitudes of the plurality of integer harmonics of the heart rate except for the integer harmonic of the heart rate having the largest integer harmonic amplitude value among the plurality of integer harmonics of the heart rate to yield a numerator, and
dividing the numerator by the denominator.
12. A method for characterizing a circulating blood volume in an animal body in a response to at least one stress, the method comprising:
characterizing a first circulating blood volume by: receiving, by a computing device, a first biological signal emulating an arterial pulse wave from a sensor associated with the animal body,
calculating, by the computing device, a first plurality of integer harmonics of a heart rate from the first biological signal wherein each of the first plurality of integer harmonics is characterized by a first integer harmonic amplitude,
calculating from the plurality of first integer harmonic amplitudes of the heart rate, by the computing device, at least one first derived parameter in a frequency domain comprising a first measure of total harmonic distortion, and
characterizing the first circulating blood volume by comparing, by the computing device, the at least one first derived parameter to a first baseline value; applying at least one stress to the animal body;
determining a measure of a second circulating blood volume by:
receiving, by the computing device, a second biological signal emulating an arterial pulse wave from a sensor associated with the animal body,
calculating, by the computing device, a second plurality of integer harmonics of a heart rate from the second biological signal, wherein each of the second plurality of integer harmonics is characterized by a second integer harmonic amplitude,
calculating from the plurality of second integer harmonic amplitudes of the heart rate, by the computing device, at least one second derived parameter in a frequency domain comprising a second measure of total harmonic distortion, and characterizing the second circulating blood volume by comparing, by the computing device, the at least one second derived parameter to a second baseline value; and comparing, by the computing device, the characterization of the first circulating blood volume to the characterization of the second circulating blood volume to characterize the circulating blood volume as a response to the at least one stress.
13. The method of claim 12, wherein the animal is a human.
14. The method of claim 12, wherein applying at least one stress comprises reducing the animal's circulatory volume during dialysis.
15. The method of claim 12, wherein applying at least one stress comprises reducing a blood volume of the animal.
PCT/US2014/028167 2013-03-15 2014-03-14 System and method for characterizing circulatory blood flow WO2014143962A2 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP14762395.3A EP2967502A4 (en) 2013-03-15 2014-03-14 System and method for characterizing circulatory blood flow
AU2014227994A AU2014227994A1 (en) 2013-03-15 2014-03-14 System and method for characterizing circulatory blood flow
CA2904682A CA2904682A1 (en) 2013-03-15 2014-03-14 System and method for characterizing circulatory blood flow

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US13/839,534 2013-03-15
US13/839,534 US9002440B2 (en) 2010-07-08 2013-03-15 System and method for characterizing circulatory blood flow

Publications (3)

Publication Number Publication Date
WO2014143962A2 WO2014143962A2 (en) 2014-09-18
WO2014143962A3 WO2014143962A3 (en) 2015-04-09
WO2014143962A4 true WO2014143962A4 (en) 2015-05-28

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PCT/US2014/028167 WO2014143962A2 (en) 2013-03-15 2014-03-14 System and method for characterizing circulatory blood flow

Country Status (4)

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EP (1) EP2967502A4 (en)
AU (1) AU2014227994A1 (en)
CA (1) CA2904682A1 (en)
WO (1) WO2014143962A2 (en)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9173579B2 (en) 2010-07-08 2015-11-03 Intelomed, Inc. System and method for characterizing circulatory blood flow
WO2014197582A1 (en) 2013-06-04 2014-12-11 Intelomed, Inc Hemodynamic risk severity based upon detection and quantification of cardiac dysrhythmia behavior using a pulse volume waveform
US10568583B2 (en) 2013-06-11 2020-02-25 Intelomed, Inc. Methods and systems for predicting hypovolemic hypotensive conditions resulting from bradycardia behavior using a pulse volume waveform
WO2015023692A1 (en) * 2013-08-12 2015-02-19 Intelomed, Inc. Methods for monitoring and analyzing cardiovascular states
WO2017177128A1 (en) 2016-04-08 2017-10-12 The Trustees Of Columbia University In The City Of New York Systems and methods for deep reinforcement learning using a brain-artificial intelligence interface
WO2018033546A1 (en) * 2016-08-18 2018-02-22 Koninklijke Philips N.V. Blood-pressure management
CN108186000B (en) * 2018-02-07 2024-04-02 河北工业大学 Real-time blood pressure monitoring system and method based on ballistocardiogram signal and photoelectric signal
CN112888359B (en) * 2018-12-24 2023-08-01 深圳迈瑞生物医疗电子股份有限公司 Interface display method for medical monitoring equipment and medical monitoring equipment
CN117476241B (en) * 2023-12-28 2024-04-19 柏意慧心(杭州)网络科技有限公司 Method, computing device and medium for determining a blood flow of a blood vessel

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US6261235B1 (en) 1993-01-07 2001-07-17 Seiko Epson Corporation Diagnostic apparatus for analyzing arterial pulse waves
JP3409399B2 (en) 1993-11-30 2003-05-26 セイコーエプソン株式会社 Medication control device
EP1905352B1 (en) * 1994-10-07 2014-07-16 Masimo Corporation Signal processing method
WO1998002090A1 (en) * 1996-07-17 1998-01-22 Cambridge Heart, Inc. Generation of localized cardiac measures
US6361501B1 (en) * 1997-08-26 2002-03-26 Seiko Epson Corporation Pulse wave diagnosing device
US8251912B2 (en) 2003-03-12 2012-08-28 Yale University Method of assessing blood volume using photoelectric plethysmography
US8057400B2 (en) * 2009-05-12 2011-11-15 Angiologix, Inc. System and method of measuring changes in arterial volume of a limb segment
US9173579B2 (en) * 2010-07-08 2015-11-03 Intelomed, Inc. System and method for characterizing circulatory blood flow

Also Published As

Publication number Publication date
AU2014227994A1 (en) 2015-09-17
WO2014143962A3 (en) 2015-04-09
WO2014143962A2 (en) 2014-09-18
EP2967502A2 (en) 2016-01-20
CA2904682A1 (en) 2014-09-18
EP2967502A4 (en) 2016-11-16

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