WO2018092986A2 - Procédé de diagnostic du système nerveux autonome fœtal et de l'état de l'activité cardiaque - Google Patents

Procédé de diagnostic du système nerveux autonome fœtal et de l'état de l'activité cardiaque Download PDF

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Publication number
WO2018092986A2
WO2018092986A2 PCT/KR2017/001908 KR2017001908W WO2018092986A2 WO 2018092986 A2 WO2018092986 A2 WO 2018092986A2 KR 2017001908 W KR2017001908 W KR 2017001908W WO 2018092986 A2 WO2018092986 A2 WO 2018092986A2
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Prior art keywords
fetal
fetus
signal
electrocardiogram
heart rate
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PCT/KR2017/001908
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English (en)
Korean (ko)
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WO2018092986A9 (fr
Inventor
임기무
김유석
김윤년
이정호
김대광
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Industry Academic Cooperation Foundation of Keimyung University
Industry Academic Cooperation Foundation of Kumoh National Institute of Technology
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Industry Academic Cooperation Foundation of Keimyung University
Industry Academic Cooperation Foundation of Kumoh National Institute of Technology
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Publication of WO2018092986A2 publication Critical patent/WO2018092986A2/fr
Publication of WO2018092986A9 publication Critical patent/WO2018092986A9/fr
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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
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/344—Foetal cardiography
    • 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate
    • 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate
    • A61B5/02411—Measuring pulse rate or heart rate of foetuses
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • 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
    • A61B5/7225—Details of analogue processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
    • 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
    • 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

Definitions

  • the present invention relates to a method for diagnosing autonomic nervous system and cardiac activity of a fetus, and more particularly, to separate fetal signals from an ECG obtained in the abdomen of a pregnant woman, Fetal autonomic nervous system and cardiac activity to separate fetal autonomic nervous system and cardiac activity by measuring fetal electrocardiogram by separating fetal ECG and EMG signals
  • the present invention relates to a method for diagnosing a condition.
  • Fetal heart rate variability is a major indicator of fetal cardiovascular function, which is controlled by the autonomic nervous system. Under normal physiological conditions, the beat-to-beat interval of the fetus's heart changes constantly with slight differences. These irregularly appearing beat-to-beat changes vary in size and direction with a periodicity, and thus the beat-to-beat change oscillates around the average level of fetal heart rate.
  • the fetal heart rate (FHR) is normal at 155 bpm in early pregnancy and at the end of gestation at an average of 135-140 bpm. FHR rises when the sympathetic nerve is stimulated and decreases FHR when the parasympathetic nerve is stimulated.
  • Fetal heart rate variability shows an increase of 3 to 5 bpm per minute when the fetal arousal or behavioral state (fetal) is present.
  • the cause of the increase in FHRV is when the fetus is awakened or manifested.
  • FHRV decreases in some cases, such as transient sleep conditions, fetal asphyxia, hypoxia, acidosis, analgesics, neurostabilizers, and anesthesia.
  • Patent Document 1 discloses a "fetal health evaluation method and apparatus", the fetal health evaluation method according to this, the process of detecting a biological signal from the mother's abdomen And extracting fetal ECG data from the detected signal, reading a fetal heart rate variability (HRV) signal from the extracted fetal ECG data, and reading the read fetal heart rate variation signal.
  • the method includes subdividing frame by frame, nonlinear analysis of the fetal heartbeat variance signal for each frame, and recognizing the fetal health state based on the nonlinear analysis result.
  • the fetal heartbeat variability (HRV) signal is subdivided by frame, and by evaluating the health status of the fetus based on the entropy information obtained by nonlinear analysis by a predetermined cycle, the conventional analog It may be possible to estimate fetal ECG signals more accurately and to be able to effectively reduce unwanted noise or to improve the signal-to-noise ratio, but to recognize fetal health using only fetal ECG signals. As a result, there is a problem that it is difficult to recognize a case where there is an abnormality in another part of the fetus (for example, the autonomic nervous system).
  • HRV fetal heartbeat variability
  • the present invention was created in view of the above situation, and separates the fetal signal from the ECG obtained from the abdomen of the pregnant woman, and the ECG and electrocardiogram of the fetus from the acquired signal of the fetus.
  • e calculating fetal heart rate (FHR 0 ) and fetal heart rate variability (FHRV) by measuring the RR peak in the normal fetal ECG based on the acquired fetal ECG;
  • the method may further include processing an EMG signal using a band filter and a moving average filter (MAF) to obtain a smoother signal for the acquired EMG signal.
  • a band filter and a moving average filter MAF
  • the original signal in acquiring the original signal through the electrocardiograph in step a), the original signal may be acquired in real time through a single channel electrocardiograph which may be worn (mounted) on the body.
  • the obtained original signal is separated into individual signals by ECG and ECG signals of the pregnant woman and the fetus, and may be separated into individual signals through a blind source separation (BSS) method.
  • BSS blind source separation
  • a singular value decomposition (SVD) algorithm and a moving average filter (MAF) may be applied to the extracted fetal signal to acquire and separate an ECG and an EMG signal of the fetus.
  • SVD singular value decomposition
  • MAF moving average filter
  • the EMG signal By measuring the fetal ECG at the time of detecting the fetal womb, there is an advantage that can accurately diagnose the autonomic nervous system and heart activity of the fetus.
  • FIG. 1 is a flowchart illustrating an execution process of a method for diagnosing autonomic nervous system and cardiac activity of a fetus according to an embodiment of the present invention.
  • FIG. 2 is a signal processing flowchart of a pregnant woman abdominal electrocardiograph for diagnosing the fetal autonomic nervous system.
  • FIG. 3 is a diagram illustrating R-R peaks and intervals in an ECG signal.
  • FIG. 1 is a flowchart illustrating an execution process of a method for diagnosing autonomic nervous system and cardiac activity state of a fetus according to an embodiment of the present invention
  • FIG. 2 is a signal processing flowchart of a pregnant woman abdominal electrocardiograph for diagnosing fetal autonomic nervous system.
  • the method of diagnosing autonomic nervous system and cardiac activity state of the fetus according to the present invention, the electrocardiogram and electrocardiogram of the pregnant woman and the fetus are mixed from the abdomen of the pregnant woman using an electrocardiogram (not shown). Acquire a signal (steps S101 and S201).
  • the original signal in acquiring the original signal through the electrocardiograph, the original signal may be acquired in real time through a single channel electrocardiograph which may be worn (mounted) on the body.
  • the obtained original signal is separated into the ECG and EMG signals of the pregnant woman and the fetus, that is, the individual signals, respectively, using a predetermined signal separation method, and the ECG and ECG of the pregnant woman are removed from the separated signal.
  • the signals may be separated into individual signals through a blind source separation (BSS) method.
  • BSS blind source separation
  • a specific filter is applied to the extracted fetal signal to acquire and separate ECG and EMG signals of the fetus (steps S104 and S204).
  • an ECG and EMG signal of the fetus may be obtained and separated by applying a singular value decomposition (SVD) algorithm and a moving average filter (MAF) to the extracted fetal signal.
  • the method may further include processing the EMG signal using a band pass filter and a moving average filter (MAF) to obtain a smoother signal with respect to the acquired EMG signal.
  • the heart rate of the normal heart is measured through the fetus's electrocardiogram.
  • the ECG also detects EMG signals in real time.
  • the fetal heart rate (FHR 0 ) and the fetal heart rate variability (FHRV) are measured by measuring the RR peak (RR interval) as shown in FIG. 3 in the normal fetal ECG based on the acquired fetal ECG. It calculates (step S105, S205-S207).
  • the ECG is recorded from the time of detection of the fetus, the ECG after the detection time of the fetus, likewise As shown in FIG. 3, the RR peak (RR interval) is measured to calculate fetal heart rate (FHR R ) and fetal heart rate variability (FHRV) (steps S106 and S207 to S210).
  • FHR R fetal heart rate
  • FHRV fetal heart rate variability
  • the calculated fetal heart rate (FHR 0 ) of the normal fetus, fetal heart rate (FHR R ) after the detection of the fetus, and fetal heart rate variability (FHRV) of the fetus after the detection of the normal and fetuses are analyzed.
  • the autonomic nervous system response and cardiac activity are diagnosed (steps S107, S211).
  • FHRV fetal heart rate variability
  • SDHR Standard Deviation of NN interval
  • RMSSD Root Mean Square of the Successive Differences
  • SDNN is the standard deviation of the NN intervals. This is the simplest variable and is the square root of the variance. Since variance is mathematically equivalent to the overall power of spectral analysis, SDNN reflects all the cycle factors responsible for the variation in the recording cycle. In most studies, SDNN is calculated over 24 hours, including the shortest high frequency variation, as well as the lowest frequency component that can be seen in 24 hours. Since the total variance of heart rate variability increases with the length of the record to be analyzed, it is not suitable for statistical quantification on shortly drawn ECGs. In fact, the longer the SDNN, the higher the SDNN value, so it is not appropriate to compare data with different recording times. Therefore, when comparing with each other like most heart rate variations, the recording time should be the same.
  • SDNN is the average of the 5 minute standard deviations, so if you record 24 hours, it is the average of 288 NN standard deviations. Clinically low SDNNs serve as predictors of high mortality in cardiovascular disease.
  • RMSSD is the sum of the squares of the differences between adjacent NN intervals, which is expressed as the square root of them.
  • the difference between adjacent NN intervals is expressed as follows.
  • RMSSD can be expressed by the following mathematical relationship.
  • This variable is well known for short-term cardiac variability, indicates sympathetic nerve activity, and is closely associated with sudden death and atrial fibrillation in epilepsy.
  • FHR does not recover but is delayed and recovered
  • the method of diagnosing autonomic nervous system and cardiac activity of the fetus separates the signal of the fetus from the ECG obtained from the abdomen of the pregnant woman, and obtains the signal of the fetus from the signal of the fetus.
  • ECG electrocardiogram
  • the method of diagnosing autonomic nervous system and cardiac activity of the fetus separates the signal of the fetus from the ECG obtained from the abdomen of the pregnant woman, and obtains the signal of the fetus from the signal of the fetus.

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  • Health & Medical Sciences (AREA)
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  • Gynecology & Obstetrics (AREA)
  • Pregnancy & Childbirth (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

La présente invention concerne un procédé de diagnostic d'un système nerveux autonome fœtal et de l'état de l'activité cardiaque qui comprend les étapes consistant à : acquérir un signal brut de l'abdomen d'une femme enceinte à l'aide d'un électrocardiographe, le signal brut comprenant un mélange de l'électrocardiogramme et de l'électromyogramme de la femme enceinte et de l'électrocardiogramme et de l'électromyogramme du fœtus ; séparer le signal brut acquis en signaux individuels relatifs à l'électrocardiogramme et l'électromyogramme de la femme enceinte et à l'électrocardiogramme et l'électromyogramme du fœtus, respectivement, et à retirer l'électrocardiogramme et l'électromyogramme de la femme enceinte du signal séparé ; extraire un signal fœtal par l'obtention de la différence entre le signal brut et le signal duquel l'électrocardiogramme et l'électromyogramme de la femme enceinte ont été retirés ; acquérir et séparer le signal relatif à l'électrocardiogramme et l'électromyogramme du fœtus du signal fœtal extrait ; mesurer le pic R-R de l'électrocardiogramme fœtal pendant une durée normale sur la base de l'électrocardiogramme fœtal acquis, et calculer la fréquence cardiaque fœtale et la variabilité de la fréquence cardiaque fœtale ; enregistrer l'électrocardiogramme à partir d'une durée de détection de mouvement fœtal sur la base du signal d'électromyogramme fœtal acquis, mesurer le pic R-R à partir de l'électrocardiogramme après la durée de détection de mouvement fœtal, et calculer la fréquence cardiaque fœtale et la variabilité de la fréquence cardiaque fœtale ; et diagnostiquer la réaction du système nerveux autonome fœtal et l'activité cardiaque par analyse de la fréquence cardiaque fœtale calculée pendant une durée normale, de la fréquence cardiaque fœtale après la détection de mouvement fœtal, de la variabilité de fréquence cardiaque fœtale pendant une durée normale, et de la variabilité de fréquence cardiaque fœtale après la détection de mouvement fœtal.
PCT/KR2017/001908 2016-11-15 2017-02-21 Procédé de diagnostic du système nerveux autonome fœtal et de l'état de l'activité cardiaque Ceased WO2018092986A2 (fr)

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KR1020160152146A KR20180055019A (ko) 2016-11-15 2016-11-15 태아의 자율신경계 및 심장활동 상태 진단방법
KR10-2016-0152146 2016-11-15

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114027852A (zh) * 2021-11-11 2022-02-11 浙江智柔科技有限公司 宫内胎儿状况分析装置和方法
CN114159040A (zh) * 2021-12-30 2022-03-11 徐智策 一种具备预警功能的胎心监护仪及监护方法

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112869724B (zh) * 2021-01-19 2022-04-22 西安交通大学 一种基于多通道被动式采集信号的胎儿健康监测仪
KR20250108940A (ko) 2024-01-09 2025-07-16 주식회사 클레어오디언스 청진신호를 통한 태아위치 확인 시스템 및 장치

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114027852A (zh) * 2021-11-11 2022-02-11 浙江智柔科技有限公司 宫内胎儿状况分析装置和方法
CN114159040A (zh) * 2021-12-30 2022-03-11 徐智策 一种具备预警功能的胎心监护仪及监护方法

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WO2018092986A9 (fr) 2018-08-16

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