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。     

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。     

Fetal heart rate monitoring based on independent component analysis

In this paper, an algorithm based on independent component analysis (ICA) for extracting the fetal heart rate (FHR) from maternal abdominal electrodes is presented. Three abdominal ECG channels are used to extract the FHR in three steps: first preprocessing procedures such as DC cancellation and low-pass filtering are applied to remove noise. Then the algorithm for multiple unknown source extraction (AMUSE) algorithm is fed to extract the sources from the observation signals include fetal ECG (FECG). Finally, FHR is extracted from FECG. The method is shown to be capable of completely revealing FECG R-peaks from observation leads even with a SNR=-200dB using semi-synthetic data.     

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.     

基于独立成分和小波分析的胎儿心电提取

背景：在胎儿心电信号的采集过程中,会受到母体和其他噪声的强干扰,如何快捷与有效地提取出胎儿心电将成为重要的研究课题。 目的：采用结合独立成分分析和小波分析的方法对来自于同一母体的观测信号进行独立分量分离,得到有效的胎儿心电。 方法：结合独立成分分析和小波分析的算法进行胎儿心电的特征提取,首先对含噪信号进行小波变换,去除奇异信号和非平稳随机信号,然后对小波重构后的信号运用快速独立成分分析算法进行成分分析。 结果与结论：在胎儿心电信号的采集过程中,会受到母体和其他噪声的强干扰,但这些信号都是随机的,不相关的,可以认为它们间是相互独立的。采用结合独立成分和小波分析的方法对来自于同一母体的观测信号进行独立分量分离,得到有效的胎儿心电。实验证明该方法是一种有效的方法。     

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。     

1519例胎儿心电图的临床价值和相关因素分析

目的对1519例胎儿全部实行常规胎儿心电图(FECG)监测工作,探讨胎儿心电图应用情况,并对异常FECG结合临床,进行临床原因分析.方法采用随机湘样方法,应用杭州产FECG-D型胎儿心电图分析仪进行监测.结果发现采用横导联方式进行监测检出率为53.5%:在孕22w进行监测检出率为45.8%;异常FECG检出率为7.64%.结论对1519例FECG的监测发现采用横导联方式并在孕22w～26w期间进行监测检出率最高、波形效果好.并对监测发现的导致FECG异常改变的临床原因与胎儿宫内窘迫的关系进行浅要分析.     

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.     

400例围产胎儿心电图检测分析及异常心电图的处理

本文应用ＦＥＣＧ－Ｄ型仪对４００例围产胎儿进行了ＦＥＣＧ的检测及分析。结果成功３６３例，成功率为９０．８％，正常ＦＥＣＧ３１６例占成功数的８７％，异常ＦＥＣＧ４７例占成功数的１３％。在对异常ＦＥＣＧ的类型及原因的分析中发现，异常ＦＥＣＧ中以ＦＳＴ下移＞５ｕｖ为多占５３．２％，其次为胎儿心动过速２５．６％，胎儿心动过缓１０．６％。胎儿心律不齐６．３％，ＦＱＲＳ时限增宽４．３％。胎儿心电图异常的原因为胎儿窘迫占７８．７％，脐带绕颈１２．８％，提示胎儿宫内缺氧是引起围产ＦＥＣＧ异常的主要原因，２２例（４７％）异常ＦＥＣＧ分别经胎盘给药、吸氧、输液等处理转为正常。     

Ultra-low-noise instrumentation and computer-based data acquisition and processing system for obtaining a noninvasive and intrauterine catheter fetal electrocardiogram

A fetal electrocardiogram (FECG) from the abdominal surface will be from 20 microVpp to unmeasurable. The intrauterine catheter signal will be from 50 microVpp to unmeasureable and will be corrupted with a significant direct current component of 10 to 200 microV. For electrophysiological information to be obtained from the abdominal and intrauterine catheter signals, the signals must be in a 0.05 to 100.0 Hz bandwidth. Because typical adult electrocardiogram systems have a noise specification of 5 to 10 microVpp from instrumentation, these systems are unacceptable for obtaining a FECG via the intrauterine catheter or noninvasively. Therefore, custom instrumentation has been developed with a noise specification of approximately 1.5 microVpp in a 0.05 to 100.0 Hz bandwidth. Design details of the custom instrumentation will be presented along with a laptop computer based data acquisition and signal processing system using LabVIEW. In addition, clinical data from the intrauterine catheter and noninvasive abdominal wall are presented to determine the feasibility of obtaining a FECG via the custom instrumentation. Clinical data obtained and documented indicates that after maternal electrocardiogram cancellation, a FECG with a good signal-to-noise ratio can be obtained in a diagnostic bandwidth of 0.05 to 100.0 Hz. Because the diagnostic bandwidth is preserved, electrophysiological information can be determined along with heart rate.     

独立分量分析及其在生物医学工程中的应用

:独立分量分析 ( Independent Component Analysis,简记 ICA)是信号分解技术的新发展。ICA与 PCA(主分量分析 )或 SVD(奇异值分解 )的主要不同是 :后者分解得的各分量只是互不相关 ,而前者则要求各分量相互统计独立。体表测量得的信号往往包含若干相对独立的成分 ,因此采用ICA技术来分解 ,所得结果往往更有生理意义 ,有利于去除干扰和伪迹。本文简短地回顾 ICA的基本原理、判据、算法和其在生物医学工程中的应用 ,并作出展望及指出存在问题。     

基于经验模态分解自适应滤波的胎儿心电信号提取

目的提出了一种基于经验模态分解自适应滤波的胎儿心电信号提取法。方法首先利用经验模态分解算法对孕妇腹部信号进行分解得到一组内模函数(IMF),然后将这组IMF作为自适应滤波器的主输入信号,并将孕妇胸部信号作为参考输入信号。通过学习算法自适应组合IMF,滤除母体心电信号成分,从而提取胎儿心电信号。结果与结论基于仿真和临床的实验结果表明,该方法提取的胎儿心电信号误差小,性能优于传统的最小均方和归一化最小均方自适应滤波算法。     

Feature extraction of ECG signal

This paper deals with new approaches to analyse electrocardiogram (ECG) signals for extracting useful diagnostic features. Initially, elimination of different types of noise is carried out using maximal overlap discrete wavelet transform (MODWT) and universal thresholding. Next, R-peak fiducial points are detected from these noise free ECG signals using discrete wavelet transform along with thresholding. Then, extraction of other features, viz., Q waves, S waves, P waves, T waves, P wave onset and offset points, T wave onset and offset points, QRS onset and offset points are identified using some rule based algorithms. Eventually, other important features are computed using the above extracted features. The software developed for this purpose has been validated by extensive testing of ECG signals acquired from the MIT-BIH database. The resulting signals and tabular results illustrate the performance of the proposed method. The sensitivity, predictivity and error of beat detection are 99.98%, 99.97% and 0.05%, respectively. The performance of the proposed beat detection method is compared to other existing techniques, which shows that the proposed method is superior to other methods.     

基于多分辨分析与连续小波变换提取和分析兔体感诱发电位

研究单次提取兔体感诱发电位,并定位和分析诱发电位波形成分。麻醉兔,以0.5Hz频率电脉冲刺激兔下肢隐神经,3764Hz采样率收集兔头皮电位。采用一维多分辨分析提取兔体感诱发电位,并用连续小波变换定位和分析诱发电位波形成分。单次诱发电位的小波变换与叠加平均诱发电位比较,表明Daubechies小波多分辨分析可以单次提取诱发电位。连续小波变换能够精确定位诱发电位中波形成分,并可采用连续小波变换分析诱发成分的频域特性。连续小波变换技术把一维时域信号投影到二维时频空间研究将成为医学信号处理的一个有用方法。     

Blood pressure waveform analysis by means of wavelet transform

The assessment of cardiovascular function by means of arterial pulse wave analysis (PWA) is well established in clinical practice. PWA is applied to study risk stratification in hypertension, with emphasis on the measurement of the augmentation index as a measure of aortic pressure wave reflections. Despite the fact that the prognostic power of PWA, in its current form, still remains to be demonstrated in the general population, there is general agreement that analysis and interpretation of the waveform might provide a deeper insight in cardiovascular pathophysiology. We propose here the use of wavelet analysis (WA) as a tool to quantify arterial pressure waveform features, with a twofold aim. First, we discuss a specific use of wavelet transform in the study of pressure waveform morphology, and its potential role in ascertaining the dynamics of temporal properties of arterial pressure waveforms. Second, we apply WA to evaluate a database of carotid artery pressure waveforms of healthy middle-aged women and men. Wavelet analysis has the potential to extract specific features (wavelet details), related to wave reflection and aortic valve closure, from a measured waveform. Analysis showed that the fifth detail, one of the waveform features extracted applying the wavelet decomposition, appeared to be the most appropriate for the analysis of carotid artery pressure waveforms. What remains to be assessed is how the information embedded in this detail can be further processed and transformed into quantitative data, and how it can be rendered useful for automated waveform classification and arterial function parameters with potential clinical applications.     

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.     

Quantification of the fetal electrocardiogram using averaging technique

A signal analysis procedure is described for obtaining time intervals parameters of the fetal electrocardiogram as recorded from the maternal abdomen. Applying averaging to the fetal electrocardiogram quantification of the PR interval, QRS duration and QT interval were measured. This technique which includes the subtraction of an averaged maternal ECG waveform using cross-correlation function and fast Fourier transform algorithm, enables the detection of all the fetal QRS complexes in spite of their coincidence with the maternal ECGs. Results that were obtained from 21 pregnant women at the gestational age of 32-41 weeks and an example of a recording with fetal premature ventricular contractions are presented. This method shows an important improvement with respect to detection of fetal heart rate and detection of arrhythmia disturbances in the fetal ECG. The averaging procedure can be used to evaluate long-lived alterations in the fetal ECG.     

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。     

Maternal microchimerism in healthy adults in lymphocytes, monocyte/macrophages and NK cells

During pregnancy some maternal cells reach the fetal circulation. Microchimerism (Mc) refers to low levels of genetically disparate cells or DNA. Maternal Mc has recently been found in the peripheral blood of healthy adults. We asked whether healthy women have maternal Mc in T and B lymphocytes, monocyte/macrophages and NK cells and, if so, at what levels. Cellular subsets were isolated after fluorescence activated cell sorting. A panel of HLA-specific real-time quantitative PCR assays was employed targeting maternal-specific HLA sequences. Maternal Mc was expressed as the genome equivalent (gEq) number of microchimeric cells per 100,000 proband cells. Thirty-one healthy adult women probands were studied. Overall 39% (12/31) of probands had maternal Mc in at least one cellular subset. Maternal Mc was found in T lymphocytes in 25% (7/28) and B lymphocytes in 14% (3/21) of probands. Maternal Mc levels ranged from 0.9 to 25.6 and 0.9 to 25.3 gEq/100,000 in T and B lymphocytes, respectively. Monocyte/macrophages had maternal Mc in 16% (4/25) and NK cells in 28% (5/18) of probands with levels from 0.3 to 36 and 1.8 to 3.2 gEq/100,000, respectively. When compared to fetal Mc, as assessed by quantification of male DNA in women with sons, maternal Mc was substantially less prevalent in all cellular subsets; fetal Mc prevalence in T and B lymphocytes, monocyte/macrophages and NK cells was 58, 75, 50 and 62% (P=0.01, P=0.005, P=0.04, P=0.05) respectively. In summary, maternal Mc was identified among lymphoid and myeloid compartments of peripheral blood in healthy adult women. Maternal Mc was less frequent than fetal Mc in all cellular subsets tested. Studies are needed to investigate the immunological effects and function of maternal Mc and to explore whether maternal Mc in cellular subsets has biological effects on her progeny.