WO2022169020A3 - Method and apparatus for pain evaluation based on ppg-based spectrogram and cnn - Google Patents

Method and apparatus for pain evaluation based on ppg-based spectrogram and cnn Download PDF

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Publication number
WO2022169020A3
WO2022169020A3 PCT/KR2021/002696 KR2021002696W WO2022169020A3 WO 2022169020 A3 WO2022169020 A3 WO 2022169020A3 KR 2021002696 W KR2021002696 W KR 2021002696W WO 2022169020 A3 WO2022169020 A3 WO 2022169020A3
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WO
WIPO (PCT)
Prior art keywords
ppg
spectrogram
cnn
pain evaluation
pain
Prior art date
Application number
PCT/KR2021/002696
Other languages
French (fr)
Korean (ko)
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WO2022169020A2 (en
Inventor
신항식
임지연
최병문
노규정
Original Assignee
전남대학교산학협력단
울산대학교 산학협력단
재단법인 아산사회복지재단
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Application filed by 전남대학교산학협력단, 울산대학교 산학협력단, 재단법인 아산사회복지재단 filed Critical 전남대학교산학협력단
Publication of WO2022169020A2 publication Critical patent/WO2022169020A2/en
Publication of WO2022169020A3 publication Critical patent/WO2022169020A3/en

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    • 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
    • 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
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • 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
    • A61B5/4824—Touch or pain perception evaluation
    • 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
    • A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/042—Knowledge-based neural networks; Logical representations of neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • 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

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Artificial Intelligence (AREA)
  • Animal Behavior & Ethology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Veterinary Medicine (AREA)
  • Surgery (AREA)
  • Mathematical Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Cardiology (AREA)
  • Signal Processing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computational Linguistics (AREA)
  • Fuzzy Systems (AREA)
  • Databases & Information Systems (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Hospice & Palliative Care (AREA)
  • Pain & Pain Management (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The present invention relates to a method and apparatus for pain evaluation based on a PPG-based spectrogram and a CNN. The method for pain evaluation based on a PPG-based spectrogram and a CNN, according to an embodiment of the present invention, may comprise the steps of: (a) acquiring a photoplethysmographic (PPG) signal of a user; (b) generating a spectrogram of the PPG signal from the acquired PPG signal; and (c) evaluating the user's pain by using the spectrogram of the PPG signal.
PCT/KR2021/002696 2021-02-08 2021-03-04 Method and apparatus for pain evaluation based on ppg-based spectrogram and cnn WO2022169020A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR1020210017756A KR20220114351A (en) 2021-02-08 2021-02-08 A method and apparatus for pain assessment based on a photoplethysmographic based spectrogram and convolutional neural network
KR10-2021-0017756 2021-02-08

Publications (2)

Publication Number Publication Date
WO2022169020A2 WO2022169020A2 (en) 2022-08-11
WO2022169020A3 true WO2022169020A3 (en) 2022-10-06

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2021/002696 WO2022169020A2 (en) 2021-02-08 2021-03-04 Method and apparatus for pain evaluation based on ppg-based spectrogram and cnn

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KR (1) KR20220114351A (en)
WO (1) WO2022169020A2 (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170135631A1 (en) * 2007-11-14 2017-05-18 Medasense Biometrics Ltd. System and method for pain monitoring using a multidimensional analysis of physiological signals
KR20190128933A (en) * 2018-05-09 2019-11-19 연세대학교 산학협력단 Emotion recognition apparatus and method based on spatiotemporal attention
KR20200016658A (en) * 2018-08-07 2020-02-17 주식회사 딥바이오 System and method for medical diagnosis using neural network
KR102197112B1 (en) * 2020-07-20 2020-12-31 주식회사 아이메디신 Computer program and method for artificial neural network model learning based on time series bio-signals

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20150093109A (en) 2014-02-06 2015-08-17 김학경 Display method of patient self-assessment of pain

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170135631A1 (en) * 2007-11-14 2017-05-18 Medasense Biometrics Ltd. System and method for pain monitoring using a multidimensional analysis of physiological signals
KR20190128933A (en) * 2018-05-09 2019-11-19 연세대학교 산학협력단 Emotion recognition apparatus and method based on spatiotemporal attention
KR20200016658A (en) * 2018-08-07 2020-02-17 주식회사 딥바이오 System and method for medical diagnosis using neural network
KR102197112B1 (en) * 2020-07-20 2020-12-31 주식회사 아이메디신 Computer program and method for artificial neural network model learning based on time series bio-signals

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
YUN ZHAO; FRANKLIN LY; QINGHANG HONG; ZHUOWEI CHENG; TYLER SANTANDER; HENRY T. YANG; PAUL K. HANSMA; LINDA PETZOLD: "How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 23 September 2020 (2020-09-23), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081770822 *

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Publication number Publication date
KR20220114351A (en) 2022-08-17
WO2022169020A2 (en) 2022-08-11

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