基于独立成分分析和量子粒子群算法的胎儿心电提取

胎儿心电图(FECG)是反映胎儿心脏电生理活动的一项客观指标,获取的FECG受到母体心电图(MECG)的干扰,如何快捷、有效的提取FECG成为重要的研究课题。在非侵入方式下,FECG的提取算法中独立成分分析(ICA)算法被认为是效果最好的方法,但现有求解其分解矩阵的算法收敛性能都不太高。量子粒子群(QPSO)算法是一种收敛于全局的智能优化算法。因此,提出了一种结合QPSO的ICA方法。研究结果表明,与其他在非侵入方式下的主要提取算法相比,这种方法能更清晰准确地提取出有用信号,为胎儿的健康检测提供了更好的方法。     

一种基于单通道腹部信号的胎儿心电提取算法

设计一种基于单通道孕腹部信号的胎儿心电提取算法,分别提取出母亲心电和胎儿心电,并计算出母亲心率和胎儿心率。首先对单通道孕腹部信号进行k-TEO(k=19)变换,突出母亲心电的QRS波,从而通过简单的阈值法确定母亲心电的R波位置,接着通过在相邻R波间重采样以获得相同的R-R间期T,这样经过一个间隔为T的梳状滤波器就可以分离出相同R-R间期的母亲心电,然后再一次在相邻R波间进行重采样恢复原来的R-R间期就可以获得实际的母亲心电了。原始腹部信号减去上面提取的母亲心电后,胎儿心电QRS波的信噪比大大提高,通过再次应用提取母亲心电的算法即可得到“干净”的胎儿心电波形。选取Physionet数据库中的8 组(26 通道)孕腹部信号数据进行分析,计算每个通道数据的胎儿心电QRS波位置识别灵敏度、阳性检测率和准确性。结果表明,胎儿心电QRS波的识别准确率达到87.1%,其中有6 个通道达到100%。另外计算每个通道的母亲心率和胎儿心率并做统计分析,发现每一组中各个通道的母亲平均心率和胎儿平均心率都非常接近,同一组中各通道间母亲平均心率最大误差为0.1次/min, 而胎儿平均心率最大误差也只有0.9次/min,进一步证明算法的可靠性。     

基于RLS-ANC自适应滤波的FECG信号提取方法

本文应用RLS-ANC(recursive least squares adaptive noise canceⅡation)自适应滤波方法提取胎儿心电(FECG)信号.该方法采用RLS-ANC自适应滤波消除母亲心电,提取胎儿心电信号.实验结果表明,本方法适应非平稳信号的能力强,收敛速度快,提取效果好于NLMS(normalized least mean squares)算法.     

A Comparison of Single Channel Fetal ECG Extraction Methods

The abdominal electrocardiogram (ECG) provides a non-invasive method for monitoring the fetal cardiac activity in pregnant women. However, the temporal and frequency overlap between the fetal ECG (FECG), the maternal ECG (MECG) and noise results in a challenging source separation problem. This work seeks to compare temporal extraction methods for extracting the fetal signal and estimating fetal heart rate. A novel method for MECG cancelation using an echo state neural network (ESN) based filtering approach was compared with the least mean square (LMS), the recursive least square (RLS) adaptive filter and template subtraction (TS) techniques. Analysis was performed using real signals from two databases composing a total of 4 h 22 min of data from nine pregnant women with 37,452 reference fetal beats. The effects of preprocessing the signals was empirically evaluated. The results demonstrate that the ESN based algorithm performs best on the test data with an F1 measure of 90.2% as compared to the LMS (87.9%), RLS (88.2%) and the TS (89.3%) techniques. Results suggest that a higher baseline wander high pass cut-off frequency than traditionally used for FECG analysis significantly increases performance for all evaluated methods. Open source code for the benchmark methods are made available to allow comparison and reproducibility on the public domain data.     

两导心电信号独立分量分析算法的研究

根据独立分量分析(ICA)理论,要想在观测信号中提取出独立分量,观测信号的数目必须大于或等于独立分量的数目,因此要求采用ICA算法的胎儿心电图机导联数必须大于一定数目,但在实际应用中常常难以满足这个条件。故本文提出了一种基于少数导联心电(ECG)信号的胎儿心电(FECG)提取算法,结合FECG和自适应噪声抵消算法,从两导采集于孕妇腹部体表的ECG信号中提取FECG。实验表明,该方法能够获得清晰的FECG信号。     

基于扩展卡尔曼滤波和奇异值分解算法的单通道胎儿心电提取方法

提出一种将扩展卡尔曼滤波(EKF)算法和奇异值分解(SVD)算法相结合的单通道胎儿心电提取方法。首先,建立母体心电的动态模型,利用该模型通过扩展卡尔曼滤波或扩展卡尔曼平滑(EKS),从孕妇的单通道腹部信号中估计出母体心电成分,然后与单通道腹部信号相减得到胎儿心电信号的初步估计,随后再利用奇异值分解算法,对初步估计出的胎儿心电信号进行去噪处理,以期得到高信噪比的胎儿心电信号。另外,针对胎儿心律不齐的情况,在奇异值分解算法中提出一种改进的心电信号重构矩阵构造方法。对合成腹部信号和实际腹部信号(源于DaISy数据库和PhysioNet中的非侵入式胎儿心电数据库,共计49个腹部通道的数据),进行胎儿心电提取实验。结果表明,使用EKF+SVD或EKS+SVD的算法比单独使用EKF或EKS的算法,提取出的胎儿心电信号的信噪比提高约5 dB,胎儿心电提取的准确性分别达95.60%和95.94%。结合EKF和SVD算法的单通道胎儿心电提取方法,可以有效地提高胎儿心电信号的信噪比和提取的准确性,并且适用于母体或胎儿心律不齐的情况。     

Assessment of autonomic function in the late term fetus: The effects of sex and state

Researchers have reported associations between fetal sex and heart rate (FHR) and heart rate variability (FHRV) but rarely in the context of fetal behavioral sleep state. We examined differences in measures of fetal autonomic function by sex and sleep state. Fetal abdominal ECG monitoring technology was used to measure FHR and two measures of FHRV—standard deviation of FHR (SD) and beat-to-beat variability (RMSSD). FHR and movement patterns were also recorded with standard Doppler ultrasound monitor technology employed to code sleep states. Data were collected from 82 healthy fetuses ranging from 36 to 39 weeks gestation. A one-way MANOVA showed that FHR was significantly lower and SD was significantly higher for males than females. Independent samples t tests found that these sex differences were only in the active sleep state. There were no significant differences in RMSSD by sex. Repeated measures MANOVA for a subset that exhibited more than one state (N = 22) showed that SD was significantly different by state. RMSSD showed a marginally significant sleep state difference. In conclusion, fetal sex differences in HR and HRV may indicate more mature autonomic functioning in near-term males than females and fetal sleep state can influence abdominal fECG derived measures of FHR and FHRV.     

The fetal electrocardiogram by independent component analysis and wavelets

Once the fetal electrocardiogram (FECG) waveforms from ECG on the maternal abdomen are detected, the fetal P wave and T wave cannot always be identified by using continuous wavelet transform (CWT). We took noninvasive FECG from the maternal abdomen, extracted it from the maternal electrocardiogram waveforms after an Independent Component Analysis (ICA), and identified the features of those waveforms by using CWT. We also simultaneously analyzed the observed signals by Primary Component Analysis (PCA). FECG has been extracted by ICA from 25 of 30 pregnant women. The fetal P wave and T wave could be identified in 21 of the 25 cases. FECG was extracted by PCA in only one case. ICA is superior to PCA, whose separation quality highly depends on the careful positioning of the electrodes. We believe that after ICA, FECG obtained by the wavelet theory based method will become a powerful tool for the differential diagnosis of fetal arrhythmias.     

基于快速定点独立分量分析算法的母胎心电信号分离

研究快速定点独立分量分析方法在母胎心电信号分离中的应用。采用此算法,在胎儿心电信号与母体心电信号可以视为相互独立的信号源的前提下,对来源于同一孕妇的观测信号进行独立分量分离。快速定点独立分量算法可以有效地分离出单个独立分量,得到的胎儿心电信号(FECG)较理想。采用独立分量分析方法,实现母胎心电信号分离,是一种值得尝试的信号处理方法。     

胎儿心电监护系统的改进与提高

作者介绍一种先进的胎儿心电监护系统，对传统的胎儿心电监护系统作了改进和提高。该系统在胎儿心电的提取与处理方法上，解决了单纯用匹配滤波法难以提取到微弱的胎儿心电信号的问题。在系统的硬件方面，优化了信号放大器，重新设计和组建一套以４８０ＰＣ机为核心的胎儿监护系统。在软件上，采用了基于Ｗｉｎｄｏｗｓ平台，Ｂｏｒｌａｎｄ Ｃ＋＋的面向对象的软件编程。     

基于非负盲分离的胎儿心率检测方法

胎儿心率监测是一种有效评估胎儿当前健康状况的重要参考依据。为了可以快速准确地获取胎儿心率,该文提出一种基于非负盲分离的胎儿心率检测方法。该方法首先对采集得到的腹壁信号进行预处理,平稳小波变换后重构出母亲心电信号;接着,采用相减法去除母亲心电信号,再把剩下含有噪声的胎儿心电信号通过时频变换得到Born-Jordan分布;最后,利用非负矩阵分解得到胎儿心电的特征信号,检测其R波位置求得胎儿瞬时心率。实验结果表明,该方法可以快速、准确有效地获得胎儿地瞬时心率数据。     

An application of reconfigurable technologies for non-invasive fetal heart rate extraction

This paper illustrates the use of a reconfigurable system for fetal electrocardiogram (FECG) estimation from mother's abdomen ECG measurements. The system is based on two different reconfigurable devices. Initially, a field-programmable analog array (FPAA) device implements the analog reconfigurable preprocessing for ECG signal acquisition. The signal processing chain continues onto a field-programmable gate array (FPGA) device, which contains all the communication and interfacing protocols along with specific digital signal processing blocks required for fundamental period extraction from FECG waveforms. The synergy between these devices provides the system the ability to change any necessary parameter during the acquisition process for enhancing the result. The use of a FPGA allows implementing different algorithms for FECG signal extraction, such as adaptive signal filtering. Preliminary works employ commercially available development platforms for test experiments, which suffice for the processing of real FECG signals from biomedical databases, as the presented results illustrate.     

Research of fetal ECG extraction using wavelet analysis and adaptive filtering

Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transform (SWT), and the wavelet coefficients at each scale were obtained. For each scale, the detail coefficients were processed by the LMS algorithm. The coefficient of the abdominal signal was taken as the original input of the LMS adaptive filtering system, and the coefficient of the thoracic signal as the reference input. Then, correlations of the processed wavelet coefficients were computed. The threshold was set and noise components were removed with the SSNF algorithm. Finally, the processed wavelet coefficients were reconstructed by inverse SWT to obtain fetal ECG. Twenty cases of simulated data and 12 cases of clinical data were used. Experimental results showed that the proposed method outperforms the LMS algorithm: (1) it shows improvement in case of superposition R-peaks of fetal ECG and maternal ECG; (2) noise disturbance is eliminated by incorporating the SSNF algorithm and the extracted waveform is more stable; and (3) the performance is proven quantitatively by SNR calculation. The results indicated that the proposed algorithm can be used for extracting fetal ECG from abdominal signals.     

基于盲信号分离的胎儿心电提取

本文提出了用盲信号分离提取胎儿心电的方法。首先研究了孕妇心电导联的特性 ,然后在此基础上设计了一个胎儿心电实时监护系统。由于使用了实时的盲信号分离算法 ,胎儿心电可以实时的被提取。一些试验结果表明该系统是有效的     

Complete foetal ECG morphology recording by synchronised adaptive filtration

Present noninvasively measured indices of foetal stress are indirect and not sufficient. Foetal electrocardiography (FECG) is a potential noninvasive measurement of the foetus wellbeing which has been little utilised because of the difficulties of measuring it. The development of time-sequenced adaptive filters which are synchronised to the QRS complex by the use of Doppler echocardiography allowed the recording of relatively noise-free FECG. The paper describes the use of this technique for obtaining the complete complex of the FECG. Several sets of time-sequenced adaptive filters are combined to allow a multilead abdominal recording to produce a measurement system which rejects maternal ECG and enhances the FECG. Five subjects have been analysed, and their FECGs have been accurately reproduced with minimal changes of the filters' parameters.     

基于非线性时间序列分析的胎儿心电信号提取

研究一种基于非线性时间序列分析的方法——非线性状态空间局部投影消噪算法来提取胎儿心电信号,在对胎儿心电信号进行分析的基础上提出胎儿心电提取的基本方案,采用改进的虚假邻点法及自相关函数法确定嵌入维数m及延迟时间τ,并对邻域半径r及局部嵌入流形维数Q的选取进行了说明。通过对实际母婴混合信号的仿真实验,验证了该方法的有效性。     

Compact long-term recorder for the transabdominal foetal and maternal electrocardiogram

Foetal heart rate (FHR) monitoring is a proven means of assessing foetal health during the antenatal period. Currently, the only widely available instrumentation for producing these data is based on Doppler ultrasound, a technology that is unsuitable for long-term use. For nearly a century, it has been known that the foetal electrocardiogram (FECG) can be detected using electrodes placed on the maternal abdomen. Although these signals suggest an alternative means of FHR derivation, their use has been limited owing to problems of poor signal-to-noise ratio. However, the eminent suitability of the transabdominal FECG for long-term FHR monitoring has suggested that perseverance with the technique would be worthwhile. The paper describes the design, construction and use of a compact, long-term recorder of three channels of 24 h antenatal transabdominal data. Preliminary use of the recorder in around 400 short recording sessions demonstrates that FHR records of equivalent quality to those from Doppler ultrasound-based instruments can be extracted from such data. The success of FHR derivation is, on average, around 65% of the recording period from around 20 weeks gestation (although this figure is reduced from around 28–32 weeks, and the success rates exhibit a wide range when individual subjects are considered). These results demonstrate that the technique offers, not only a means of acquiring long-term FHR data that are problematic to obtain by other means, but also a more patient-friendly alternative to the Doppler ultrasound technique.     

基于DSP的自适应胎儿心电图仪研究

介绍了一种自适应胎儿心电图仪的研究与实现方法.研制了TMS320LF2407A数字信号处理芯片为核心的嵌入式系统.根据自适应噪声抵消(Adaptive noise cancelling,ANC)原理,研究与实现了自适应噪声抵消软件算法,无创无损提取胎儿心电信号,并通过通讯接口送至上位机实时显示,分析和记录处理结果.实验表明该仪器设计合理,性能良好.     

Real-time multichannel abdominal fetal ECG monitor using Digital Signal CoProcessor

A real-time multichannel fetal ECG monitor based on a personal computer (PC) and a MOTOROLA DSP56001 Digital Signal CoProcessor (DSP) is introduced. The DSP board is plugged into the PC, which functions as a HOST computer. An analog 8 Leads Interface and Analog to Digital circuits module is connected to the DSP through a synchronous, opticalisolated communication channel.

The fetal ECG detection is based on a cross-correlation technique. An averaged maternal ECG waveform is generated using a cross-correlation alignment procedure and a user-defined template. The fetal ECG signals present in the maternal waveform is suppressed during the averaging procedure, since both are uncorrelated. The average maternal ECG waveform is then subtracted from the abdominal real time signals, and maternal-free fetal ECGs signals are obtained, including fetal QRS complexes that coincide with maternal ones. Using the abdominal ECGs signals after subtraction, an averaged fetal waveform is generated. The maternal and the fetal heart rate are calculated during the process.

The algorithm described above can be performed in real time on up to eight abdominal ECG traces by the DSP, and the desired results are passed to the HOST PC, to be stored and displayed. Electrodes positioning procedures for detecting the fetal QRS complexes with the best signal to noise ratio are not needed. Using the multichannel system, the user can select the best channel for fetal QRS detection, and accurate results for the heart rate signal are obtained. Averaged fetal waveforms are obtained from all the leads.     

基于自适应线性神经网络的胎儿心电信号提取

胎儿心电信号提取对胎儿监护具有重要意义。本文介绍了一种基于自适应线性神经网络的胎儿心电信号提取方法。该方法根据母体心电信号与母体腹部信号的相关性原理,以母体心电信号为网络输入,母体腹部信号为网络目标,采用W-H学习方法获取的训练误差即为提取出的胎儿心电信号。此外,通过增加网络隐含层,对神经网络的结构进行改进,增加网络训练精度,从而得到更好的训练结果,提取出更易识别的胎儿心电信号。最后分别使用仿真数据和临床数据对上述方法进行测试,实验结果表明,利用自适应线性神经网络可以提取出胎儿心电信号,通过改进神经网络结构,可以提取出更为清晰的胎儿心电信号。