WO2014021515A1 - Procédé et appareil pour l'évaluation de la santé de fœtus - Google Patents

Procédé et appareil pour l'évaluation de la santé de fœtus Download PDF

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Publication number
WO2014021515A1
WO2014021515A1 PCT/KR2012/010672 KR2012010672W WO2014021515A1 WO 2014021515 A1 WO2014021515 A1 WO 2014021515A1 KR 2012010672 W KR2012010672 W KR 2012010672W WO 2014021515 A1 WO2014021515 A1 WO 2014021515A1
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Prior art keywords
signal
fetal
frame
fetus
entropy
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PCT/KR2012/010672
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English (en)
Korean (ko)
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박인양
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가톨릭대학교 산학협력단
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Publication of WO2014021515A1 publication Critical patent/WO2014021515A1/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
    • A61B5/02—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
    • A61B5/02405—Determining heart rate variability
    • 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
    • A61B5/02411—Detecting, measuring or recording 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
    • A61B5/02—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
    • A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
    • 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

Definitions

  • the present invention relates to fetal health evaluation by using the fetal ECG data extracted from the mother's abdomen and using the entropy value obtained through nonlinear analysis thereof.
  • the monitoring of the fetal condition is essential for mothers associated with gestational hypertension, gestational diabetes mellitus, and low birth weight infants, and it is necessary to continuously examine the condition of the fetus from prenatal to analgesia.
  • the present invention provides a method for evaluating fetal health, which is capable of estimating the fetal ECG signal more accurately than the analog method of printing fetal heart rate on paper, and effectively analyzing unwanted noise or improving signal-to-noise ratio. To provide.
  • Fetal health evaluation method detects the bio-signal from the mother's abdomen, amplifies the detected bio-signal and removes the noise and outputs the ECG data of the fetus from the output signal Extracting and converting the extracted ECG data of the fetus into a digital signal, subdividing the fetal heart rate variability (HRV) signal read out from the converted signal by frame, and fetal heart rate variation signal by frame It includes a process of recognizing the health state of the fetus based on the entropy information (entropy information) obtained by non-linear analysis for each predetermined cycle.
  • HRV fetal heart rate variability
  • the electrode unit for detecting the bio-signal from the mother abdomen, the ECG data of the fetus from the detected bio-signal separated from the maternal abdominal bio-signal extracted and extracted A biosignal detection unit that reads a fetal heart rate variability (HRV) signal from electrocardiogram data, a frame generation for subdividing the read fetal heart rate variance signal by frame, and spectral normalization of the HRV signal for each frame
  • HRV fetal heart rate variability
  • An analysis unit configured to calculate an entropy value for each frame of the HRV signal normalized by the analysis unit, and a non-linear analysis of the fetal heart rate variability (HRV) signal for each frame by a predetermined period. Health status of the fetus based on the above non-linear analysis results And a controller to recognize.
  • the present invention can not only estimate the fetal ECG signal more accurately than the conventional method of printing the fetal heart rate on paper, but also effectively reduce unwanted noise or improve the signal-to-noise ratio.
  • FIG. 1 is a whole flow diagram of the fetal health evaluation method according to an embodiment of the present invention.
  • Figure 2 is a flow chart for performing non-linear analysis in the fetal health evaluation method according to an embodiment of the present invention.
  • Figure 3 (a) is a raw signal (raw signal) for the heartbeat variance signal of the fetus, (b) is a graph showing the signal interpolated through the Fast Fourier Transform (FFT) from the raw signal.
  • FFT Fast Fourier Transform
  • FIG. 4 (a) shows data index signal intervals which are preset and extracted from data indexes 11 to 15 corresponding to signal loss (5) at a size 65 to 80 bpm (bit per minute) of the local region in the fetal heartbeat data region.
  • (B) is a graph which interpolated the said (a).
  • 5 is a cutoff frequency versus Shannon entropy graph quantified by Shannon entropy according to the data index K of the cutoff frequency for the fetal heartbeat variance signal according to the change of the cutoff frequency according to an embodiment of the present invention.
  • FIG. 6 is a block diagram of a fetal health evaluation apparatus according to an embodiment of the present invention.
  • Fetal health evaluation method detects the bio-signal from the mother's abdomen, amplifies the detected bio-signal and removes the noise and outputs the ECG data of the fetus from the output signal Extracting and converting the extracted ECG data of the fetus into a digital signal, subdividing the fetal heart rate variability (HRV) signal read out from the converted signal by frame, and fetal heart rate variation signal by frame It includes a process of recognizing the health state of the fetus based on the entropy information (entropy information) obtained by non-linear analysis for each predetermined cycle.
  • HRV fetal heart rate variability
  • Fetal health evaluation apparatus is an electrode unit for detecting a bio-signal from the mother abdomen, the ECG data of the fetus from the detected bio-signal separated from the maternal abdominal bio-signal extracted and the extracted ECG of the fetus
  • a biosignal detection unit for reading a fetal heart rate variability (HRV) signal from the data, a frame generation for subdividing the read fetal heart rate variance signal by frame, and an analysis for performing spectral normalization of the HRV signal for each frame
  • HRV fetal heart rate variability
  • an entropy calculating unit calculating a frame-specific entropy value for the HRV signal normalized by the analyzer, and controlling the frame rate fetal heart rate variability (HRV) signal to be linearly analyzed for each predetermined period.
  • HRV fetal heart rate variability
  • FIG. 1 is an overall flowchart of a fetal health evaluation method according to an embodiment of the present invention.
  • a biosignal is detected from a mother's abdomen in step 110.
  • the detected biosignal is amplified by an amplifying unit and a filter unit, and the noise is removed and output.
  • the biosignal detection is performed through at least two electrodes attached to the mother's abdomen.
  • the ECG data of the fetus is extracted from the output signal, and the extracted ECG data of the fetus is converted into an analog time series data (time series date) through an A / D converter in step 116.
  • the fetal heartbeat variation signal read from the converted signal is subdivided into frames, and in step 120, the non-linear analysis of the fetal heartbeat variation signal for each frame is performed at predetermined intervals.
  • the heartbeat transition signal is obtained from a signal measured by an M-mode ultrasonic Doppler method.
  • FIG. 3A is a raw signal of a fetal heartbeat variance signal, and (B) is interpolated from the original signal through a Fast Fourier Transform (FFT).
  • FFT Fast Fourier Transform
  • FIG. 2 is a flow chart for performing the non-linear analysis in the fetal health evaluation method according to an embodiment of the present invention, in step 210 to the fetal heartbeat variance signal From the time series signal, information about a predetermined data index signal interval is extracted from the remaining sections except for the zero subsection in step 212 except for a zero subsection in the data index.
  • FIG. 4A the operation process of 210 and 212 is shown in FIG. 4A.
  • signal loss (5) is performed at a size of 65 to 80 bpm (local per region) in the fetal heartbeat data region of FIG. 3.
  • step 214 spectral normalization is performed on the extracted information, and in step 216, an entropy value for each frame of the heartbeat variance signal is calculated from the normalization distribution.
  • step 214 performing spectral normalization in step 214, fast Fourier transform the fetal heartbeat variance signal, obtain a spectrum from the fast Fourier transform, and then determine a cutoff frequency of the spectrum.
  • the cutoff frequency determination of the spectrum is performed by quantifying a distribution of a predetermined data index signal interval difference signal by using Shannon entropy (COF-SE), where the slope of the trajectory of the Shannon entropy exceeds a preset threshold. The frequency is determined as the cutoff frequency for the high frequency noise of the heartbeat transition signal.
  • COF-SE Shannon entropy
  • step 122 entropy information of the fetal heartbeat signal for each frame is obtained by performing the operation of step 120.
  • the health status of the fetus is evaluated based on the obtained entropy information.
  • fetal heartbeat variation is evaluated by using approximate entropy.
  • each of the labors was delivered using the FHR records immediately before delivery of the fetus in three different ways of delivery: vaginal delivery in the second analgesia, planned cesarean delivery before analgesia, and emergency cesarean delivery during the first analgesia.
  • vaginal delivery in the second analgesia in the second analgesia
  • planned cesarean delivery before analgesia planned cesarean delivery before analgesia
  • emergency cesarean delivery during the first analgesia The fetal heart rate variability entropy index at different stages was compared.
  • Corometrics 150 (Corometrics, CT, USA), Doppler ultrasound cardiotocography and autocorrelation function were used for FHR signal acquisition.
  • the pulse repetition frequency was 2 Hz
  • the pulse duration was 92 Hz
  • the heart rate counting range was 50-210 beats per minute. All records were saved to a connected PC and further offline analysis was performed.
  • FHR signals measured during the last few minutes of delivery may be lost or contaminated.
  • Known preprocessing algorithms were used for the preprocessing of the signals.
  • Spline interpolation was used to replace the filtered heartbeat during signal loss periods of 2 seconds or less. For longer periods, we replaced the most recent segment of the same length with no signal loss.
  • All heart rate data in bpm were converted into RR intervals for entropy calculations. Heart rate (bpm) can be expressed in 60 / RR interval (seconds).
  • Nonlinear assays for FHR variability have been important in fetal cardiovascular and endocrine function.
  • FHR variability was examined using Approximate Entropy, a mathematical nonlinear indicator.
  • ApEn quantifies the complexity of FHR variability. Lower ApEn values indicate lower complexity, while higher ApEn values indicate higher complexity. Summarize the algorithm as follows:
  • the size of the new time series ( ) Is N-m + 1, and the size of each vector is m. Also select the threshold distance or the comparison length r. Two vectors of size m And ) Has a distance less than r:
  • Vector of distance (r), size (m) ) Is a vector of the same size ( ) Is the same as
  • the mean ( ⁇ standard deviation (STD)) maternal age of the asphyxia delivery group, emergency cesarean section group, and selective cesarean section group was 31 ( ⁇ 3), 32 ( ⁇ 3) and 33 ( ⁇ 4) years, respectively.
  • P 0.013
  • the mean maternal age of the asphyxia delivery group was younger than the other two groups.
  • the linear index including the mean FHR, STD, coefficient of variation (CV), and variance index (DI) was found to be significantly different for each delivery method in all time segments.
  • the RR interval of the asphyxia delivery group was significantly longer and varied than the RR interval of other groups. This result is consistent with the results of other linear measurements such as CV and DI. Pairwise comparisons show that the linear indices of the RR intervals in the vaginal delivery group, the emergency cesarean section group, and the choking delivery group and the optional cesarean section group are significantly different in all time segments (except for the average index of the first five minutes). It is present.
  • Nonlinear exponents including ApEn and SampEn in different time segments of different delivery modes are shown in Table 3.
  • the pairwise comparison (after applying the Bonferroni correction) showed that there was a significant difference in mean ApEn and SampEn between the vaginal delivery group and the selective cesarean section group in all time segments. At the 2000 RR interval, significant differences were also detected between the mean ApEn and SampEn intervals between the choking delivery group and the emergency cesarean section.
  • the FHR entropy index of the second analgesic phase was significantly lower than that of the first analgesic and analgesic phase.
  • the last 5 minutes of fetus of analgesia were much lower in FHR entropy index than the first 5 minutes of analgesia.
  • FIG. 6 is a block diagram of the fetal health evaluation apparatus according to an embodiment of the present invention.
  • the apparatus 600 to which the present invention is applied includes an electrode unit 610, a signal detector 612, an analyzer 614, a controller 616, an entropy calculator 618, and an A / D converter ( 620 and the frame generator 622.
  • the electrode unit 610 detects a biosignal from a maternal abdomen.
  • the biosignal detection unit 612 amplifies the biosignal detected from the electrode unit 610 and removes noise.
  • the control unit 616 extracts the fetal ECG data from the maternal abdominal biosignal in the signal output from the signal detector 612 and converts the fetal ECG data into a digital signal, thereby reading the fetal heartbeat variation read from the converted signal (Heart).
  • Rate Variability (HRV) signal is controlled to be non-linear analysis and output to recognize the fetal health state based on the obtained entropy information.
  • the controller 616 extracts information of a predetermined data index signal section from the remaining sections except for a section in which a data index is less than zero, from the time series signal for the fetal heartbeat variance signal, and extracts the information.
  • Spectral normalization is performed on the received information, and the control is performed to calculate an entropy value for each frame of the heartbeat variance signal from the normalization distribution, thereby performing nonlinear analysis.
  • the cutoff frequency of the spectrum may be determined by quantifying the distribution of a predetermined data index signal interval difference signal by using Shannon entropy (COF-SE) to determine a frequency at a point where the slope of the Shannon entropy exceeds a preset threshold.
  • COF-SE Shannon entropy
  • the A / D converter 620 converts the ECG data of the fetus extracted under the control of the controller 616 into a digital signal.
  • the frame generator 622 subdivides the HRV signal read out from the converted signal for each frame.
  • the analyzer 614 performs spectral normalization on the HRV signal for each frame.
  • the entropy calculator 618 calculates an entropy value for each frame of the HRV signal normalized from the analyzer 614.
  • the present invention not only can estimate the fetal ECG signal more accurately, but also can perform nonlinear analysis according to the rapid change of the input signal using the entropy change information, thereby effectively reducing the unwanted noise or improving the signal-to-noise ratio. To make it possible.

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Abstract

La présente invention concerne un procédé pour l'évaluation de la santé d'un fœtus, comprenant les étapes de : détection d'un biosignal à partir de l'abdomen d'une mère ; amplification du biosignal détecté et élimination du bruit afin de produire en sortie ce dernier ; extraction des données d'électrocardiogramme d'un fœtus à partir du signal de sortie et conversion des données d'électrocardiogramme extraites d'un fœtus en un signal numérique ; et acquisition de l'état de santé d'un fœtus sur la base de l'information de l'entropie obtenue par segmentation, par image, du signal de la variabilité de la fréquence cardiaque (HRV) d'un fœtus lu à partir du signal converti, et de l'analyse non linéaire, par durée prédéfinie, du signal HRV par image.
PCT/KR2012/010672 2012-07-30 2012-12-11 Procédé et appareil pour l'évaluation de la santé de fœtus WO2014021515A1 (fr)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104161508A (zh) * 2014-08-28 2014-11-26 哈尔滨工程大学 一种胎儿心电信号提取方法
CN107625519A (zh) * 2017-09-20 2018-01-26 武汉中旗生物医疗电子有限公司 心电图处理方法及装置
CN107684422A (zh) * 2016-08-05 2018-02-13 深圳先进技术研究院 一种胎儿心电分离方法及装置
US10368755B2 (en) 2013-06-25 2019-08-06 The Research Foundation For The State University Of New York Apparatus and method for feature extraction and classification of fetal heart rate

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101630071B1 (ko) 2014-10-24 2016-06-14 한국표준과학연구원 태아 바이오데이터 기반 태아 성장상태 분석방법 및 분석시스템

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5442940A (en) * 1991-10-24 1995-08-22 Hewlett-Packard Company Apparatus and method for evaluating the fetal condition
WO2000054650A2 (fr) * 1999-03-15 2000-09-21 The Johns Hopkins University Appareil et procede passifs et non invasifs pour surveiller la frequence cardiaque foetale
US20010014776A1 (en) * 1994-09-21 2001-08-16 Nancy E. Oriol Fetal data processing system and method employing a time-frequency representation
KR20030077367A (ko) * 2002-03-26 2003-10-01 학교법인 포항공과대학교 심박동 변이 신호에 포함된 고주파 잡음 제거를 위한컷오프 주파수 결정 방법
US20100274145A1 (en) * 2009-04-22 2010-10-28 Tupin Jr Joe Paul Fetal monitoring device and methods

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5442940A (en) * 1991-10-24 1995-08-22 Hewlett-Packard Company Apparatus and method for evaluating the fetal condition
US20010014776A1 (en) * 1994-09-21 2001-08-16 Nancy E. Oriol Fetal data processing system and method employing a time-frequency representation
WO2000054650A2 (fr) * 1999-03-15 2000-09-21 The Johns Hopkins University Appareil et procede passifs et non invasifs pour surveiller la frequence cardiaque foetale
KR20030077367A (ko) * 2002-03-26 2003-10-01 학교법인 포항공과대학교 심박동 변이 신호에 포함된 고주파 잡음 제거를 위한컷오프 주파수 결정 방법
US20100274145A1 (en) * 2009-04-22 2010-10-28 Tupin Jr Joe Paul Fetal monitoring device and methods

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10368755B2 (en) 2013-06-25 2019-08-06 The Research Foundation For The State University Of New York Apparatus and method for feature extraction and classification of fetal heart rate
CN104161508A (zh) * 2014-08-28 2014-11-26 哈尔滨工程大学 一种胎儿心电信号提取方法
CN107684422A (zh) * 2016-08-05 2018-02-13 深圳先进技术研究院 一种胎儿心电分离方法及装置
CN107625519A (zh) * 2017-09-20 2018-01-26 武汉中旗生物医疗电子有限公司 心电图处理方法及装置

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