基于小波分析与自适应滤波的胎儿心电提取

摘要

Objective To extract fetal ECG by a combined algorithm of wavelet analysis and adaptive filtering from the abdominal signal of the pregnant woman. Methods Stationary wavelet transform was used to decompose the signals from maternal abdomen and chest into five slices. Then LMS algorithm was introduced at each level of the wavelet coefficients. At last, the fetal ECG could be obtained by wavelet reconstruction. Results Clinical data were used to test the method. The results indicated that the combination of wavelet analysis and adaptive filtering could identify fetal ECG from maternal abdominal signal. Conclusion Compared with LMS algorithm, the result is better especially when the waveform of maternal ECG coincides with fetal ECG. What's more, as this method is simple and easy to implement, it keeps a superiority of realtime capability.%目的:利用小波分析与自适应滤波算法相结合从母体腹部信号中提取胎儿心电.方法:首先对母体腹部信号和胸部信号做5层平稳小波分解,然后在每层小波系数引入最小均方误差(LMS)算法对应滤波,最后将小波系数重构获得胎儿心电.结果:使用临床数据进行验证,结果表明,基于小波分析与自适应滤波的算法能够识别母体腹部信号中的胎儿心电信号.结论:该方法与LMS算法相比提取效果更好,尤其对母体心电波形与胎儿心电波形重合部分改善明显.另外,该算法计算简单,易于实现,保持了较高的实时性.