WO2018023698A1 - 一种胎儿心电分离方法及装置 - Google Patents

一种胎儿心电分离方法及装置 Download PDF

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WO2018023698A1
WO2018023698A1 PCT/CN2016/093526 CN2016093526W WO2018023698A1 WO 2018023698 A1 WO2018023698 A1 WO 2018023698A1 CN 2016093526 W CN2016093526 W CN 2016093526W WO 2018023698 A1 WO2018023698 A1 WO 2018023698A1
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signal
ecg
fetal
abdominal wall
template
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French (fr)
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张南南
张金勇
王磊
李晖
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Shenzhen Institute of Advanced Technology of CAS
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Shenzhen Institute of Advanced Technology of CAS
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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
    • 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

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  • the invention relates to the field of biomedical engineering technology, in particular to a method and a device for separating fetal ECG, in particular to an adaptive single-lead fetal electrocardiographic separation method and device.
  • Fetal electrocardiogram is one of the most important objective indicators of intrauterine physiological activity. By analyzing fetal ECG signals, it can diagnose fetal intrauterine hypoxia, intrauterine distress and congenital heart disease. Effectively reduce the morbidity and mortality of various types of diseases in newborns. Therefore, the clinical application of the perinatal monitor will be one of the powerful measures to ensure the safety of the fetus at all stages of the perinatal period and to ensure the eugenics of the fetus.
  • the fetus is surrounded by several layers of different conductivity in the mother's abdomen, such as the placenta, amniotic fluid, maternal uterus and the subcutaneous tissue of the mother's abdomen.
  • amniotic fluid has the highest electrical conductivity
  • fetal fat has the lowest electrical conductivity.
  • the skin and subcutaneous fat of pregnant women also have weak electrical conductivity, but the electrical conductivity is about ten times smaller than that of muscle tissue.
  • Matched filtering mainly uses statistical characteristics such as autocorrelation and cross-correlation of signals, but the situation to be faced in the actual environment is much more complicated than the assumption, and the fetal ECG signal obtained by matched filtering is not Very ideal.
  • ICA Independent Component Analysis
  • Wavelet threshold denoising fetal ECG signal extraction method filtering Using wavelet transform combined with prior signal knowledge can obtain a good fetal ECG signal, but the extraction process is susceptible to amplitude and fetal ECG signal-like interference. It often leads to the occurrence of R wave miss detection and misdetection in the fetal ECG signal. It will cause errors when calculating the fetal heart rate, which is not conducive to clinical diagnosis.
  • Neural network method This method can detect the QRS complex of ECG signals according to the prediction error of the neural network.
  • the PT segment signal is flat and can be predicted better.
  • the QRS complex the difference between adjacent points is large, and the prediction error will be generated.
  • the QRS complex is predicted, and the artificial neural network is predicted.
  • the training sample is required to have a certain representativeness, which is difficult to realize in the actual abdominal wall ECG signal denoising application.
  • the traditional adaptive cancellation method requires an additional reference signal, that is, in addition to the abdominal wall electrode, an additional maternal chest lead electrode is required, and the adaptive method is used to eliminate the relevant maternal component in the chest lead and the abdominal wall lead.
  • the maternal abdominal wall ECG signal and the maternal chest lead ECG signal need to be correlated in order to be better eliminated, and the conduction path of the maternal ECG signal is very complicated.
  • the abdominal wall The maternal ECG signal and the maternal ECG signal in the chest lead are poorly correlated.
  • adaptive cancellation to extract fetal ECG signals will have a large number of maternal ECG leaks, which will cause great interference to the correct identification of fetal ECG components.
  • adaptive cancellation is still unable to achieve single-lead fetal ECG signal extraction.
  • the invention provides a method and a device for separating fetal electrocardiogram, which are used to solve the problem that the existing separation algorithm is complicated in calculation and cannot realize single lead.
  • an embodiment of the present invention provides a method for separating a fetal electrocardiogram, comprising: intercepting a segment of an ECG signal of a specific length by using a position of an R wave peak in a received abdominal wall ECG signal as a central positioning point; The ECG signal segment corresponding to the current ECG cycle and the previous M-1 consecutive ECG signal segments are linearly weighted averaged to generate a recursive template; according to the parent RQS wave group in the recursive template corresponding to the current ECG cycle Correlation of the parent QRS complex, dynamic amplitude correction of the parent QRS complex in the recursive template, generating a maternal abdominal wall ECG estimation signal; using the maternal abdominal wall ECG estimation signal as a reference signal, Maternal abdominal wall The electrical signal is used as the desired signal, and the fetal ECG signal is separated from the maternal abdominal wall ECG signal by an adaptive algorithm.
  • an embodiment of the present invention further provides a fetal electrocardiographic separation device, comprising: a segment intercepting module, configured to intercept a specific length by using a position of an R wave peak in a received abdominal wall ECG signal as a central positioning point; The ECG signal segment; the recursive template generating module is configured to perform linear weighted averaging on the ECG signal segment corresponding to the current ECG cycle and the M-1 consecutive ECG signal segments to generate a recursive template; the wave group correction module, And performing dynamic amplitude correction on the parent QRS complex in the recursive template according to the correlation between the parent RQS wave group in the recursive template and the parent QRS complex corresponding to the current ECG cycle, to generate a maternal abdominal wall An electrocardiographic estimation signal; a separation module, configured to use the maternal abdominal wall ECG estimation signal as a reference signal, and use the mother abdominal wall ECG signal as a desired signal to separate from the maternal abdominal wall ECG signal by an adaptive algorithm
  • the ECG signal segment configured to
  • the fetal electrocardiographic separation method and device proposed by the invention only need one way abdominal wall ECG signal to realize single lead; and, after repeated superimposition and weighting, the recursive template basically no longer contains fetal ECG components, and adaptive filtering
  • the algorithm eliminates the correlation between the reference signal and the main input signal, and retains the unrelated portion, so the separation of the fetal ECG signal in the abdominal wall ECG signal can be maximized; the design of the fetal separation algorithm of the present invention is simple and intuitive. For abnormal clinical data, it is easy to find the cause and add correction modules.
  • FIG. 1 is a schematic structural diagram of a system for a fetal electrocardiographic separation method according to an embodiment of the present invention
  • FIG. 2 is a schematic block diagram of an estimation mechanism of an abdominal wall mother's electrocardiogram according to an embodiment of the present invention
  • FIG. 3 is a flowchart of processing of a fetal electrocardiogram separation method according to an embodiment of the present invention
  • step S102 of the embodiment shown in FIG. 3 is a process flow diagram of step S102 of the embodiment shown in FIG. 3;
  • FIG. 5 is a schematic structural diagram of a fetal electrocardiogram separation apparatus according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a recursive template generating module 102 of the embodiment shown in FIG. 5;
  • FIG. 7 is a schematic structural diagram of a group correction module 103 of the embodiment shown in FIG. 5;
  • FIG. 8 is a waveform diagram of a 5-channel mother abdominal wall mixed ECG signal used in a specific embodiment of the present invention.
  • Figure 9 is an analysis of experimental results of a specific embodiment of the present invention.
  • embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of full hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.
  • the invention aims at estimating the mixed ECG signal extracted from the abdominal wall of the mother body, and estimating the cardiac electrocardiographic signal of the abdominal wall by the averaging method, and the leakage of the parent QRS wave group has a great influence on correctly identifying the fetal ECG component, and the present invention estimates
  • the maternal abdominal wall ECG signal is corrected by the parent QRS complex, and the corrected maternal abdominal wall signal estimator is used as the reference signal in the adaptive algorithm. Since the implementation of the method requires only one parent abdominal wall ECG signal, therefore, The invention can enable an adaptive fetal ECG signal separation scheme to be implemented in a single lead system.
  • FIG. 1 is a schematic structural diagram of a system of a fetal electrocardiographic separation method according to an embodiment of the present invention.
  • y(n) represents the acquired abdominal wall ECG signal
  • f(n) is the fetal ECG signal in the abdominal wall signal
  • x(n) is the maternal ECG signal in the abdominal wall signal
  • y( n) is the desired signal of the adaptive filter
  • x'(n) is the abdominal wall mother electrocardiogram estimated by the abdominal wall mother electrocardiographic estimation mechanism
  • the adaptive filter continuously "learns" and "tracks” the input signal, so that output signal Maximum approximation of the abdominal wall ECG signal, thus making the error signal Minimal, This is the separated fetal ECG signal.
  • two input signals are needed, namely: a parent abdominal wall ECG signal (main input signal), and an estimated abdominal wall ECG signal (reference input signal).
  • a parent abdominal wall ECG signal main input signal
  • an estimated abdominal wall ECG signal reference input signal
  • the core of the invention is how to calculate the abdominal wall mother ECG estimation signal as a reference input signal to the adaptive algorithm.
  • Fig. 2 it is a schematic block diagram of the mechanism for estimating the cardiac wall of the abdominal wall of the present invention.
  • the maternal abdominal wall signal is detected by the R wave peak point to determine the R wave peak position in the maternal abdominal wall ECG signal, and the mother abdominal wall signal is segmented according to the R wave peak position by a specific length, and the segmented signal segment is linearly weighted averaged.
  • the recursive template basically does not contain the fetal ECG component; then extracting the QRS complex of the current ECG cycle to correct the QRS complex in the recursive template to generate a maternal abdominal wall ECG estimation signal.
  • FIG. 3 is a flowchart of processing of a fetal electrocardiographic separation method according to an embodiment of the present invention. As shown in Figure 3, it includes:
  • Step S101 taking the R wave peak position in the received abdominal wall ECG signal as a central positioning point, and intercepting a specific length of the ECG signal segment;
  • Step S102 performing linear weighted averaging on the ECG signal segment corresponding to the current ECG cycle and the preceding M-1 consecutive ECG signal segments to generate a recursive template
  • Step S103 performing dynamic amplitude correction on the parent QRS complex in the recursive template according to the correlation between the parent RQS wave group in the recursive template and the parent QRS complex corresponding to the current ECG cycle, to generate a matrix Abdominal wall ECG estimation signal;
  • Step S104 the mother abdominal wall ECG estimation signal is used as a reference signal, and the mother abdominal wall ECG signal is used as a desired signal, and the fetal ECG signal is separated from the mother abdominal wall ECG signal by an adaptive algorithm.
  • step S101 of the embodiment of the present invention first, the R wave peak position in the mother abdominal wall ECG signal needs to be determined.
  • step S101 intercepting a segment of the ECG signal of a specific length, where N is the length of the segment that is intercepted, and
  • the range of values is (1.1, 1.4). Taking the position of the parent R wave peak as the positioning point, a fixed length is taken for each of the R wave peaks to form a mixed ECG template of RR ⁇ 2R-R length, and an average template is obtained for a fixed number of templates before the RR interval.
  • the choice of intercepting the length N of the segment is crucial.
  • the value range (1.1, 1.4) is to ensure that the start and end points of the segment interception fall on the TP segment of the ECG signal.
  • the signal in this segment is gentle, and the segment overlap will be averaged, avoiding the signal at the recursive template connection.
  • the magnitude difference is to ensure that the start and end points of the segment interception fall on the TP segment of the ECG signal. The signal in this segment is gentle, and the segment overlap will be averaged, avoiding the signal at the
  • the ECG signal segment corresponding to the current ECG cycle and the M-1 consecutive ECG signal segments are linearly weighted and averaged to generate a recursive template, as shown in FIG. :
  • Step S1021 linearly averaging M-1 consecutive ECG signal segments in front of the current ECG cycle to generate an average template of the first M-1 ECG signal segments.
  • y 1 (t) represents the average template of the generated first M-1 ECG signal segments
  • Representing the maternal electrocardiographic component in the average template Represents the fetal ECG component in the average template.
  • the fetal ECG and the maternal ECG are derived from two independent sources, that is, the fetal QRS complex is distributed at different locations within the maternal ECG cycle.
  • the fetal ECG component in the average template can be expressed as:
  • the maternal ECG amplitude is generally more than ten times the fetal ECG amplitude, namely:
  • y 1 (t) is the average template of the first M-1 ECG signal segments, and the estimated signal contains almost no fetal ECG signals.
  • the weighting coefficients a, b can be set by human experience.
  • the recursive template basically no longer contains fetal ECG components.
  • step S103 is used to perform dynamic amplitude correction on the parent QRS complex in the recursive template to generate a final maternal abdominal wall ECG estimation signal.
  • the present invention dynamically corrects the maternal electrocardiographic component in the recursive template based on the correlation between the parent QRS complex and the parent QRS complex in the recursive segment.
  • the method is as follows:
  • the QRS complex corresponding to the current ECG cycle is used to perform dynamic amplitude correction on the parent QRS complex in the recursive template to generate a maternal abdominal wall ECG estimation signal.
  • the estimation is more accurate and has better fetal ECG separation effect.
  • step S104 the abdominal electrode obtains the main input signal, and the estimated mother abdominal wall ECG signal is used as an input signal, and the signal substantially does not contain the fetal ECG signal, and only contains the noise to be eliminated and the mother ECG signal;
  • the electrical signal is the desired signal.
  • the adaptive algorithm eliminates the correlation between the input signal and the desired signal, and preserves the uncorrelated portion. Therefore, the fetal ECG signal separation in the abdominal wall ECG signal can be maximized.
  • the adaptive algorithm may be an adaptive least mean square (LMS) algorithm, an adaptive recursive least squares (RLS) algorithm, a least squares lattice (LSL) adaptive algorithm, or the like.
  • LMS adaptive least mean square
  • RLS adaptive recursive least squares
  • LSL least squares lattice
  • FIG. 5 is a schematic structural view of a fetal electrocardiogram separation apparatus according to an embodiment of the present invention.
  • the method includes: a segment intercepting module 101, configured to intercept a specific length of an ECG signal segment by using a received R wave peak position in a parent abdominal wall electrocardiographic signal as a center positioning point; and a recursive template generating module 102, For performing linear weighted averaging on the ECG signal segment corresponding to the current ECG cycle and the preceding M-1 consecutive ECG signal segments to generate a recursive template; the group correction module 103 is configured to: according to the parent in the recursive template Correlation of the RQS complex with the parent QRS complex corresponding to the current ECG cycle, dynamic amplitude correction of the parent QRS complex in the recursive template, to generate a maternal abdominal wall ECG estimation signal; separation module 104, The mother abdominal wall ECG signal is used as a reference signal, and the mother abdominal wall ECG signal is used as a desired signal
  • the segment intercepting module 101 takes the R wave peak position in the received abdominal wall ECG signal as a central positioning point, and intercepts a specific length of the ECG signal segment, and specifically includes:
  • the specific length of the ECG signal segment is N, and among them The range of values is (1.1, 1.4).
  • the recursive template 102 performs linear weighted averaging on the ECG signal segment corresponding to the current ECG cycle and the M-1 consecutive ECG signal segments to generate a recursive template, as shown in FIG. 6 . As shown, it specifically includes:
  • the average template generating unit 1021 linearly averages M-1 consecutive ECG signal segments in front of the current ECG cycle to generate an average template of the first M-1 ECG signal segments;
  • the group correction module 103 applies the recursive template according to the correlation between the parent RQS wave group in the recursive template and the parent QRS group corresponding to the current ECG cycle.
  • the parent QRS complex is subjected to dynamic amplitude correction to generate a maternal abdominal wall ECG estimation signal, as shown in Figure 7, which specifically includes:
  • the correlation coefficient calculation unit 1031 is configured to calculate a correlation between the QRS complex segment corresponding to the current ECG cycle and the QRS complex segment in the recursive template, and generate a correlation coefficient;
  • the dynamic correction unit 1032 is configured to perform dynamic amplitude correction on the parent QRS group in the recursive template by using the QRS complex corresponding to the current ECG cycle according to the correlation coefficient to generate a maternal abdominal wall ECG estimation signal. .
  • the separation module 104 separates a fetal ECG signal from the mother abdominal wall ECG signal by an adaptive algorithm, where the adaptive algorithm includes an adaptive least mean square algorithm, Adaptive recursive least squares algorithm, least squares lattice adaptive algorithm.
  • FIG. 8 a waveform diagram of a mixed 5-channel maternal abdominal wall ECG signal used in this embodiment is shown.
  • the data length of each signal is 2500 sample points, and the sampling rate is 250 Hz.
  • the first road abdominal wall signal is the one signal with the largest telecommunication noise ratio of the fetal heart, that is, the signal of this road is the best, and the fourth and fifth abdominal wall ECG signals can not recognize the fetal heart with the naked eye.
  • the position of the electric R peak which is not used by the algorithm of the present invention, is not considered by the algorithm of the present invention.
  • the second path signal is selected as the algorithm verification data, and the adaptive filtering adopts the adaptive recursive least squares algorithm, and the experimental result analysis is shown in FIG. 9.
  • the fetal QRS complex is far from the parent QRS complex:
  • the fetal QRS complex is far from the parent QRS complex, as indicated by a in Figure 9. As can be seen from Figure 9, the fetal QRS component is extracted and the left and right parent QRS components are suppressed. Such fetal QRS complexes and maternal The positional relationship of the QRS complex is the most common positional relationship in the abdominal wall ECG and the most easily extracted positional relationship.
  • the fetal QRS complex is adjacent to the parent QRS complex:
  • the fetal QRS complex is adjacent to the parent QRS complex, as indicated by the mark b in Fig. 9. It can be seen from Fig. 9 that the fetal QRS component is extracted in this case, and the adjacent QRS component is suppressed.
  • the identification of fetal ECG QRS complexes has an impact.
  • the positional relationship between the fetal QRS complex and the parent QRS complex is a small number of positional relationships in the abdominal wall ECG, and it is also difficult to extract the positional relationship.
  • the fetal QRS complex is completely coincident with the parent QRS complex, as indicated by the reference c in Fig. 9. As can be seen from Fig. 9, the fetal QRS component is extracted in this case, and the coincident parent QRS component is suppressed.
  • the positional relationship between the fetal QRS complex and the parent QRS complex is a small number of positional relationships in the abdominal wall ECG and the most difficult to extract positional relationship.
  • the fetal QRS complex is far from the parent QRS complex, the fetal QRS complex is adjacent to the parent QRS complex, the fetal QRS complex, and the parent QRS complex are completely coincident. , have very good extraction results.
  • the invention only needs one way of the abdominal wall electrocardiographic signal to complete the adaptive fetal signal separation.
  • two signals are needed, namely: one abdominal wall ECG signal (main input signal), one chest lead ECG signal (reference input signal), through the main input signal
  • the template recursively generates the reference signal. Therefore, only one abdominal wall ECG signal is needed in the design of the present invention, which greatly simplifies the lead system of the system.
  • the separation effect is good: since the amplitude of the maternal ECG component is more than ten times the amplitude of the fetal ECG component, the recursive template after multiple superimposition and weighting basically no longer contains the fetal ECG component; the adaptive filtering algorithm eliminates The portion of the reference signal associated with the main input signal retains the uncorrelated portion, so the separation of fetal ECG signals in the abdominal wall ECG signal can be maximized.
  • the algorithm design idea is simple and intuitive, for abnormal clinical data, easy to find the cause and add correction module.
  • the embodiment of the present invention further provides a computer readable program, wherein when the program is executed, the program causes a computer to execute the fetal electrocardiographic separation method according to the embodiment of the present invention.
  • the embodiment of the present invention further provides a storage medium storing a computer readable program, wherein the computer readable program causes the computer to execute the fetal electrocardiographic separation method according to the embodiment of the present invention.
  • the above apparatus and method of the present invention may be implemented by hardware or by hardware in combination with software.
  • the present invention relates to a computer readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to cause the logic component to implement the various methods described above Or steps.
  • the present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, or the like.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Abstract

一种胎儿心电分离方法及装置。胎儿心电分离方法包括：以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段（S101）；对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板（S102）；根据递归模板中的母体QRS波群与当前心电周期对应的母体QRS波群的相关性，对递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号（S103）；将母体腹壁心电估计信号作为参考信号，将母体腹壁心电信号作为期望信号，通过自适应算法，从母体腹壁心电信号中分离出胎儿心电信号（S104）。胎儿心电分离方法及装置的算法简单，且只需要一路母体腹壁心电信号，故可以完成单导联胎儿心电信号分离。

Description

一种胎儿心电分离方法及装置 技术领域
本发明涉及生物医学工程技术领域，尤其涉及一种胎儿心电分离方法及装置，具体的讲是一种自适应单导联胎儿心电分离方法及装置。
背景技术
本部分旨在为权利要求书中陈述的本发明的实施方式提供背景或上下文。此处的描述不因为包括在本部分中就承认是现有技术。
胎儿心电信号(Fetal electrocardiogram，FECG)是胎儿宫内生理活动最主要的客观指标之一，通过分析胎儿心电信号，能够早期诊断胎儿宫内缺氧、宫内窘迫以及先天性心脏病等，有效地降低新生儿各类疾病的发病率和死亡率。因此，围产期监护仪的临床应用将是保证围产期各个阶段的胎儿安全，保障胎儿优生的有力措施之一。
在围产期，胎儿在母体腹部由几个不同的电导率的包裹层包围，如胎盘、羊水、母体子宫和母体腹部皮下组织等，其中羊水的导电能力最高，而胎脂的导电能力最低，此外孕妇的皮肤和皮下脂肪也有微弱的导电性，但是导电能力比肌肉组织约小十倍。在采集胎儿心电时，由于胎儿心电信号需要经过上述导电层，本来就很微弱的胎儿心电信号更容易受外界的干扰。这些不同的组织，形成了所谓的“人体容积导体”，这个容积导体不是一个稳定的导体，其导电性和几何形状随着整个妊娠期不断改变。因此，这将导致母体腹部心电混合信号具有如下特点：1)信噪比低，胎儿心电分量太弱，仅为10～50uV左右，而母亲心电信号则可达750uV，两者可差十倍以上。肌电噪声与其它干扰也很强，信号完全淹没于噪声之中。2)时域中胎儿QRS波与母体QRS波有10～30％的重叠。3)频域中胎儿频谱与母体的频谱大部分重叠。4)信号随机性很强，是非平稳过程，特别是由于胎儿的自由移动造成胎儿心电传输通道的时变性。
上述的这些特点，为获得高精度的胎儿心电信号制造了比较大的障碍，因此从母体腹壁信号中提取出胎儿心电信号，以实现围产期胎儿生命信息的监护，是目前广泛研究和关注的问题。目前，对此问题的解决主要采用以下几种方法：
1)匹配滤波：匹配滤波主要利用的是信号的自相关和互相关等统计特性，但在实际环境中所要面临的情况远比假设情况要复杂的多，采用匹配滤波获得的胎儿心电信号不是很理想。
2)独立成分分析法(ICA)：需要多路腹壁信号，无法实现单导联胎儿心电信号提取。
3)小波阈值去噪的胎儿心电信号提取方法滤波：利用小波变换结合先验信号知识能够获得效果不错的胎儿心电信号，但是提取过程中容易受到幅度和胎儿心电信号类似信号的干扰，往往导致胎儿心电信号中R波漏检和误检等情况产生，在计算胎儿心率时会引起误差，不利于于临床诊断。
4)神经网络法：此方法可以根据神经网络的预测误差检测心电信号的QRS复合波。PT段信号平缓，可以被较好的预测，而对于QRS复合波，相邻点差异较大，会产生预测误差，利用这个预测误差训练网络，对QRS复合波进行预测，预测时的人工神经网络具有多层结构，利用神经网络学习训练过程需要花费较长时间，而且要求训练样本具有一定的代表性，这在实际腹壁心电信号降噪应用中很难实现。
针对上述问题，大量研究中将自适应方法用于胎儿心电分离，自适应滤波主要通过自主学习达到适应条件变化的效果。但是传统的自适应对消方法要求额外提供参考信号，即，除了腹壁电极外，还需要配备额外的母体胸导连电极，自适应方法对消掉胸导联和腹壁导联中相关的母体分量，这意味着母体腹壁心电信号和母体胸导联心电信号需要相关，才能够被较好的对消掉，并且，母体心电信号的传导路径非常复杂，某些情况下，腹壁中的母体心电信号和胸导联中的母体心电信号相关性差。因此，利用自适应对消提取胎儿心电信号会有大量的母体心电泄露，对正确识别胎儿心电分量造成了很大干扰。此外，自适应对消仍然无法实现单导联的胎儿心电信号提取。
发明内容
本发明提出一种胎儿心电分离方法及装置，用以解决现有的分离算法计算复杂且无法实现单导联的问题。
为了达到上述目的，本发明实施例提供一种胎儿心电分离方法，包括：以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心 电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
为了达到上述目的，本发明实施例还提供一种胎儿心电分离装置，包括：片段截取模块，用于以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；递归模板生成模块，用于对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；波群修正模块，用于根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；分离模块，用于将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
本发明提出的胎儿心电分离方法及装置，只需要一路腹壁心电信号，实现了单导联；并且，经过多次叠加、加权后的递归模板基本不再含有胎儿心电分量，自适应滤波算法消除了参考信号与主输入信号中相关的部分，保留不相关的部分，因此腹壁心电信号中的胎儿心电信号分离可以被最大化的提取出来；本发明的胎儿分离算法设计思路简单直观，针对于异常的临床数据，易于查找原因和添加修正模块。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例的胎儿心电分离方法的系统结构示意图；
图2为本发明实施例的腹壁母体心电估计机制的示意框图；
图3为本发明实施例的胎儿心电分离方法的处理流程图；
图4为图3所示实施例的步骤S102的处理流程图；
图5为本发明实施例的胎儿心电分离装置的结构示意图；
图6为图5所示实施例的递归模板生成模块102的结构示意图；
图7为图5所示实施例的波群修正模块103的结构示意图；
图8为本发明的具体实施例采用的5路母体腹壁混合心电信号的波形图；
图9为本发明的具体实施例的实验结果分析图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
本领域技术技术人员知道，本发明的实施方式可以实现为一种系统、装置、设备、方法或计算机程序产品。因此，本公开可以具体实现为以下形式，即：完全的硬件、完全的软件(包括固件、驻留软件、微代码等)，或者硬件和软件结合的形式。
下面参考本发明的若干代表性实施方式，详细阐释本发明的原理和精神。
本发明针对从母体腹壁提取出的混合心电信号，利用平均法对腹壁母体心电信号进行估计，针对于母体QRS波群泄露，对正确识别胎儿心电分量造成很大影响，本发明对估计后的母体腹壁心电信号进行了母体QRS波群修正，修正后的母体腹壁信号估计量，作为自适应算法中的参考信号，由于该方法的实现只需要一路母体腹壁心电信号，因此，本发明可以使基于自适应的胎儿心电信号分离方案在单导联系统下实现。
图1为本发明实施例的胎儿心电分离方法的系统结构示意图。如图1所示，y(n)表示采集到的母体腹壁心电信号，f(n)为腹壁信号中的胎儿心电信号，x(n)为腹壁信号中的母体心电信号，y(n)为自适应滤波器的期望信号，x'(n)为通过腹壁母体心电估计机制估计的腹壁母体心电，自适应滤波器对输入信号不断的进行“学习”和“跟踪”，使输出信号
Figure PCTCN2016093526-appb-000001
最大限度的逼近腹壁心电信号，从而使误差信号
Figure PCTCN2016093526-appb-000002
最小，
Figure PCTCN2016093526-appb-000003
即为分离出的胎儿心电信号。
也就是说，基于自适应的胎儿心电分离算法，需要两路输入信号，即：一路母体腹壁心电信号(主输入信号)，一路估计出的腹壁母体心电信号(参考输入信号)，这相对于现有技术中的需要接入一路胸导联心电信号作为参考输入信号，实现了单导联。
本发明的核心是如何计算出腹壁母体心电估计信号，以作为自适应算法的参考输入信号。在本发明中，如图2所示，为本发明的腹壁母体心电估计机制的示意框图。母体腹壁信号经过R波波峰点检测，确定母体腹壁心电信号中的R波波峰位置，并根据R波波峰位置采用特定长度对母体腹壁信号进行分割，分割后的信号片段进行线性加权平均 后，生成递归模板，递归模板基本不含有胎儿心电分量；然后提取当前心电周期的QRS波群对递归模板中的QRS波群做修正，生成母体腹壁心电估计信号。
图3为本发明实施例的胎儿心电分离方法的处理流程图。如图3所示，包括：
步骤S101，以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；
步骤S102，对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；
步骤S103，根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；
步骤S104，将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
在本发明实施例的步骤S101中，首先需要确定母体腹壁心电信号中的R波波峰位置，该方法为：对接收到的母体腹壁心电信号进行差分运算，以获取腹壁心电信号的斜率曲线，对斜率曲线做绝对滑动积分运算，记录每秒钟内的最大值，对前8秒内的最大值做平均，则R波判定阈值＝系数比值*前8秒内的最大值平均，对差分值大于R波判定阈值的段，进行R波波峰位置最大值查找，以确定最终的R波波峰位置点。
并且，在步骤S101中，截取特定长度的心电信号片段，N为截取的片段的长度，且
Figure PCTCN2016093526-appb-000004
Figure PCTCN2016093526-appb-000005
的取值范围为(1.1，1.4)。以母体R波波峰位置为定位点，对R波波峰左右各取固定长度，形成R-R～2R-R长度的混合心电模板，对当R-R间隔前的固定数目的模板求平均模板。其中，截取片段长度N的选择至关重要，
Figure PCTCN2016093526-appb-000006
的取值范围(1.1，1.4)是为了保证片段截取的起止点都落在心电信号的TP段，此段内信号平缓，并且片段重合部分将会被平均，避免了递归模板连接处信号较大的幅值落差。
在本发明实施例的步骤S102中，对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板，如图4所示，具体包括：
步骤S1021，对当前心电周期前面的M-1个连续的心电信号片段进行线性平均，生成前M-1个心电信号片段的平均模板。
对当前心电周期前面的M-1个连续的心电信号片段进行线性平均，生成前M-1个心电信号片段的平均模板，具体方法为：
将所述当前心电周期前面的M-1个连续的心电信号片段的R波波峰位置对齐，进行线性平均，生成平均模板：
Figure PCTCN2016093526-appb-000007
其中，y1(t)表示生成的前M-1个心电信号片段的平均模板，
Figure PCTCN2016093526-appb-000008
表示所述平均模板中的母体心电分量，
Figure PCTCN2016093526-appb-000009
表示所述平均模板中的胎儿心电分量。
由于分割片段的中心点是母体R波波峰，胎儿心电和母体心电来自于两个独立的信号源，即胎儿QRS波群分布在母体心电周期内的不同位置。
因此，平均模板中的胎儿心电分量可表示为：
Figure PCTCN2016093526-appb-000010
由于母体心电幅值一般是胎儿心电幅值的十几倍，即：
Figure PCTCN2016093526-appb-000011
因此：
Figure PCTCN2016093526-appb-000012
也就是说，y1(t)是前M-1个心电信号片段的平均模板，估计出的信号中几乎不含有胎儿心电信号
步骤S1022，根据所述当前心电周期对应的心电信号片段与所述平均模板获得递归模板＝a*平均模板+b*当前心电周期对应的心电信号片段，a，b为设定的加权系数。加权系数a，b可以由人为经验设定。
经过多次叠加、加权后的递归模板基本不再含有胎儿心电分量。
在本发明实施例中，步骤S103用以对所述递归模板中的母体QRS波群进行动态幅值修正，生成最终的母体腹壁心电估计信号。
在本发明实施例中，能否有效的抑制掉母体QRS波群分量，对正确识别分离结果中的胎儿心电分量起着决定性作用。递归模板中的母体心电波形，是对较早的心电波形和最新波形的等权累加和线性平均，估计出的母体心电片段不具有动态性。因此，本发明根据最新母体QRS波群和递归片段中母体QRS波群的相关性，对递归模板中的母体心电分量进行动态修正。
具体实施时，方法如下：
首先，计算所述当前心电周期对应的QRS波群片段与所述递归模板中的QRS波群片段的相关性，生成相关系数，具体步骤为：
(1)提取当前心电周期中的母体QRS波群片段：y3＝[y3(1),y3(2),...,y3(P)]，其中P为母体QRS波群片段的长度；
(2)提取出递归模板中母体QRS波群片段：y2＝[y2(1),y2(2),...,y2(P)]；
(3)计算当前心电周期中的母体QRS波群片段与递归模板中母体QRS波群片段的相关系数r23：
Figure PCTCN2016093526-appb-000013
其次，根据所述相关系数，用所述当前心电周期对应的QRS波群片段对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号。
所采用的表达式如下：
Figure PCTCN2016093526-appb-000014
由于对递归模板中的母体腹壁心电估计信号进行了QRS波群修正，因此估计的更精确，具有较好的胎儿心电分离效果。
在步骤S104中，腹部电极取得主输入信号，将估计出的母体腹壁心电信号作为输入信号，此信号中基本不含有胎儿心电信号，只包含欲消除的噪声和母体心电信号；腹壁心电信号为期望信号，通过自适应算法，消除了输入信号与期望信号中相关的部分，保留不相关的部分，因此腹壁心电信号中的胎儿心电信号分离可以被最大化的提取出来。
本发明实施例中，自适应算法可以为自适应的最小均方(LMS)算法、自适应的递归最小二乘方(RLS)算法、最小二乘格形(LSL)自适应算法等。
应当注意，尽管在附图中以特定顺序描述了本发明方法的操作，但是，这并非要求或者暗示必须按照该特定顺序来执行这些操作，或是必须执行全部所示的操作才能实现期望的结果。附加地或备选地，可以省略某些步骤，将多个步骤合并为一个步骤执行，和/或将一个步骤分解为多个步骤执行。
在介绍了本发明示例性实施方式的方法之后，接下来，参考图5对本发明示例性实施方式的胎儿心电分离装置进行介绍。该装置的实施可以参见上述方法的实施，重复之处不再赘述。以下所使用的术语“模块”和“单元”，可以是实现预定功能的软件和/或硬件。尽管以下实施例所描述的模块较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。
图5为本发明实施例的胎儿心电分离装置的结构示意图。如图5所示，包括：片段截取模块101，用于以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；递归模板生成模块102，用于对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；波群修正模块103，用于根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；分离模块104，用于将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
进一步地，在本发明实施例中，所述片段截取模块101以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段，具体包括：所述心电信号片段的特定长度为N，且
Figure PCTCN2016093526-appb-000015
其中
Figure PCTCN2016093526-appb-000016
的取值范围为(1.1，1.4)。
进一步地，在本发明实施例中，所述递归模板102对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板，如图6所示，具体包括：
平均模板生成单元1021，对当前心电周期前面的M-1个连续的心电信号片段进行线性平均，生成前M-1个心电信号片段的平均模板；
加权单元1022，用于根据所述当前心电周期对应的心电信号片段与所述平均模板获得递归模板＝a*平均模板+b*当前心电周期对应的心电信号片段，a，b为设定的加权系数。
进一步地，在本发明实施例中，所述波群修正模块103根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号，如图7所示，具体包括：
相关系数计算单元1031，用于计算所述当前心电周期对应的QRS波群片段与所述递归模板中的QRS波群片段的相关性，生成相关系数；
动态修正单元1032，用于根据所述相关系数，用所述当前心电周期对应的QRS波群片段对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号。
进一步地，在本发明实施例中，所述分离模块104通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号，所述自适应算法包括自适应的最小均方算法、自适应的递归最小二乘方算法、最小二乘格形自适应算法。
此外，尽管在上文详细描述中提及了胎儿心电分离装置的若干单元，但是这种划分仅仅并非强制性的。实际上，根据本发明的实施方式，上文描述的两个或更多单元的特征和功能可以在一个单元中具体化。同样，上文描述的一个单元的特征和功能也可以进一步划分为由多个单元来具体化。
以下通过一个具体实施例来说明采用本发明的胎儿心电分离方法实现胎儿心电信号分离的效果。
参看图8所示，为该具体实施例采用的5路母体腹壁混合心电信号的波形图。如图8所示，每路信号的数据长度为2500个样本点，采样率250Hz。由图8可知，第1路腹壁信号为胎母心电信噪比最大的一路信号，即此路信号效果最好，第4路和第5路腹壁心电信号用肉眼已经无法识别出胎儿心电R波峰位置，此两路信号提取效果已不能为本发明的算法所用，故不在本发明的算法的考虑范围之内。
本实施例选择第2路信号作为算法验证数据，自适应滤波采用自适应递归最小二乘方算法，其实验结果分析参看图9。
1、胎儿QRS波群远离母体QRS波群：
胎儿QRS波群远离母体QRS波群，如图9中标注a，由图9可知，这种情况下的胎儿QRS波分量被提取出，左右的母体QRS波分量被抑制掉。此种胎儿QRS波群和母体 QRS波群的位置关系，是腹壁心电中最普遍的位置关系，也是最容易提取出的位置关系。
2、胎儿QRS波群紧邻母体QRS波群：
胎儿QRS波群紧邻母体QRS波群，如图9中标注b所示，由图9可知，这种情况下的胎儿QRS波分量被提取出，紧邻的母体QRS波分量被抑制掉，并未对胎儿心电QRS波群的识别造成影响。此种胎儿QRS波群和母体QRS波群的位置关系，是腹壁心电中少数比例存在的位置关系，也是较难提取出的位置关系。
3、胎儿QRS波群和母体QRS波群完全重合：
胎儿QRS波群完全和母体QRS波群重合，如图9中标注c所示，由图9可知，这种情况下的胎儿QRS波分量被提取出，重合的母体QRS波分量被抑制掉。此种胎儿QRS波群和母体QRS波群的位置关系，是腹壁心电中少数比例存在的位置关系，也是最难提取出的位置关系。
由以上结果分析可知，通过本发明的胎儿心电分离方法，胎儿QRS波群远离母体QRS波群、胎儿QRS波群紧邻母体QRS波群、胎儿QRS波群和母体QRS波群完全重合三种情况，均有非常理想的提取效果。
本发明提出的胎儿心电分离方法及装置，具有以下有益效果：
1、单导联：本发明仅需要一路母体腹壁心电信号，即可完成基于自适应的胎儿信号分离。传统的采用基于自适应的胎儿心电信号分离算法，需要两路信号，即：一路腹壁心电信号(主输入信号)，一路胸导联心电信号(参考输入信号)，通过对主输入信号进行模板递归生成参考信号，因此，本发明设计中只需要一路腹壁心电信号，这将大大简化了系统的导联系统。
2、分离效果好：由于母体心电分量幅值是胎儿心电分量幅值的十几倍，因此经过多次叠加、加权后的递归模板基本不再含有胎儿心电分量；自适应滤波算法消除了参考信号与主输入信号中相关的部分，保留不相关的部分，因此腹壁心电信号中的胎儿心电信号分离可以被最大化的提取出来。
3、算法设计思路简单直观，针对于异常的临床数据，易于查找原因和添加修正模块。
本发明实施例还提供一种计算机可读程序，其中当执行所述程序时，所述程序使得计算机执行本发明实施例所述的胎儿心电分离方法。
本发明实施例还提供一种存储有计算机可读程序的存储介质，其中所述计算机可读程序使得计算机执行本发明实施例所述的胎儿心电分离方法。
本发明以上的装置和方法可以由硬件实现，也可以由硬件结合软件实现。本发明涉及这样的计算机可读程序，当该程序被逻辑部件所执行时，能够使该逻辑部件实现上文所述的装置或构成部件，或使该逻辑部件实现上文所述的各种方法或步骤。本发明还涉及用于存储以上程序的存储介质，如硬盘、磁盘、光盘、DVD、flash存储器等。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
本发明中应用了具体实施例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (10)

  1. 一种胎儿心电分离方法，其特征在于，包括：
    以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；
    对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；
    根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；
    将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
  2. 根据权利要求1所述的胎儿心电分离方法，其特征在于，以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段，包括：
    所述心电信号片段的特定长度为N，且
    Figure PCTCN2016093526-appb-100001
    其中
    Figure PCTCN2016093526-appb-100002
    的取值范围为(1.1，1.4)。
  3. 根据权利要求1所述的胎儿心电分离方法，其特征在于，对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板，包括：
    对当前心电周期前面的M-1个连续的心电信号片段进行线性平均，生成前M-1个心电信号片段的平均模板；
    根据所述当前心电周期对应的心电信号片段与所述平均模板获得递归模板＝a*平均模板+b*当前心电周期对应的心电信号片段，a，b为设定的加权系数。
  4. 根据权利要求3所述的胎儿心电分离方法，其特征在于，根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号，包括：
    计算所述当前心电周期对应的QRS波群片段与所述递归模板中的QRS波群片段的相关性，生成相关系数；
    根据所述相关系数，用所述当前心电周期对应的QRS波群片段对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号。
  5. 根据权利要求1所述的胎儿心电分离方法，其特征在于，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号，包括：
    所述自适应算法包括自适应的最小均方算法、自适应的递归最小二乘方算法、最小二乘格形自适应算法。
  6. 一种胎儿心电分离装置，其特征在于，包括：
    片段截取模块，用于以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段；
    递归模板生成模块，用于对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板；
    波群修正模块，用于根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性，对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号；
    分离模块，用于将所述母体腹壁心电估计信号作为参考信号，将所述母体腹壁心电信号作为期望信号，通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号。
  7. 根据权利要求6所述的胎儿心电分离装置，其特征在于，所述片段截取模块以接收到的母体腹壁心电信号中的R波波峰位置为中心定位点，截取特定长度的心电信号片段，具体包括：
    所述心电信号片段的特定长度为N，且
    Figure PCTCN2016093526-appb-100003
    其中
    Figure PCTCN2016093526-appb-100004
    的取值范围为(1.1，1.4)。
  8. 根据权利要求6所述的胎儿心电分离装置，其特征在于，所述递归模板对当前心电周期对应的心电信号片段以及前面M-1个连续的心电信号片段进行线性加权平均，生成递归模板，具体包括：
    平均模板生成单元，对当前心电周期前面的M-1个连续的心电信号片段进行线性平均，生成前M-1个心电信号片段的平均模板；
    加权单元，用于根据所述当前心电周期对应的心电信号片段与所述平均模板获得递归模板＝a*平均模板+b*当前心电周期对应的心电信号片段，a，b为设定的加权系数。
  9. 根据权利要求8所述的胎儿心电分离装置，其特征在于，所述波群修正模块根据所述递归模板中的母体RQS波群与所述当前心电周期对应的母体QRS波群的相关性， 对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号，具体包括：
    相关系数计算单元，用于计算所述当前心电周期对应的QRS波群片段与所述递归模板中的QRS波群片段的相关性，生成相关系数；
    动态修正单元，用于根据所述相关系数，用所述当前心电周期对应的QRS波群片段对所述递归模板中的母体QRS波群进行动态幅值修正，生成母体腹壁心电估计信号。
  10. 根据权利要求6所述的胎儿心电分离装置，其特征在于，所述分离模块通过自适应算法，从所述母体腹壁心电信号中分离出胎儿心电信号，所述自适应算法包括自适应的最小均方算法、自适应的递归最小二乘方算法、最小二乘格形自适应算法。
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