结合小波变换和中值滤波心电信号去噪算法研究

Research on the ECG Signal Denoising Algorithm Based on Wavelet Transform and the Median Filter

在采集心电信号数据的过程中,必然会涉及到肌电干扰、基线漂移和50Hz工频干扰,而使用常规系统辨识法则常常在一定程度上难以鉴定心电信号的特性。中值滤波器是一种操作简单的、高速的非线性信号滤波器,它常用于心电信号中低频去噪过程,如基线漂移。因为WTS的二进小波是一组带通滤波器,不同尺度有不同的频带,小波变换被选定用来分解原始信号,小波变系数的重建形成了消除干扰的心电信号。采用模拟实验是要确定如何进行自适应的阈值选取,适当的分解层数和小波函数。通过使用MIT/BIH数据库的心电信号,并结合计算机仿真形成的心电信号来对该方法进行检验。结论表明此算法可有效抑制心电信号中的主要噪声,满足心电波形临床分析和诊断的需求。

In the process of ECG signal data acquisition,it was necessary to involve the electromyographic interference,baseline drift and 50Hz interference,while using the conventional system identification rules often to some extent and was difficult to identify the characteristics of ECG signal.Median filter was a kind of simple operation,high speed nonlinear signal filter,it was commonly used in the ECG signal denoising process in low frequency,such as baseline drift.Since WTS two dyadic wavelet was a set of band-pass filters with different scales,different frequency bands.The wavelet transform was used to decompose the original signal selected.Wavelet transform coefficients of the reconstruction was formed to eliminate interference in ECG signal.The simulation experiment to determine how adaptive threshold selection,appropriate level decomposition and wavelet function.Through using the MIT/BIH database of ECG signal,and combining with the computer simulation of the formation of ECG signal on the method of testing.Conclusion shows that this algorithm can effectively restrain the main noise in ECG signals,meet the ECG waveform analysis of clinical and diagnostic requirements.