基于统计加权滑动平均的去心电信号基线漂移

基线漂移(BW)是心电(ECG)信号一种常见的干扰。为了有效去除BW而且保留更多的潜在ECG成分,本文提出了一种简单的基于统计加权滑动平均滤波器(SMA)。首先,对滑动窗口中的ECG数据进行分段,统计并确定几个具有最大概率的数据段范围ak,bk]。然后,将滑动窗口中数值属于ak,bk]采样点的权值置为1,否则为0。最后,对窗口中权值为1的采样值进行平均以估计滑动窗口的基线。通过www.physionet.org提供的共享ECG数据对该算法性能进行实验,结果表明:与传统滑动平均滤波器(MA)和小波包(WP)变换滤波相比,该算法能更有效地去除BW,而且产生的ECG扭曲最小。

Correction of electrocardiogram signal baseline wander based on statistically weighted moving average filter

Baseline wander (BW) is a common noise contaminating electrocardiogram (ECG). In order to effectively correct baseline of ECG signal and to preserve more latent components of ECG signal, this paper proposes a simple and novel filter based on statistically weighted moving average. Firstly, after the arrange between the maximum and the minimum of these sampling values in a moving window was divided into many sections with equal width, several segments a(k), b(k)] including most samples were determined. Then, for every sample point in the moving window its weight was decided according to the criterion: its weight was set as 1 if the sampling value belongs to a(k), b(k)], otherwise, as 0. Lastly, all these ECG sampling points with 1 weight were averaged to estimate the real baseline in the moving window. The algorithm was tested by simulated signal and real signal from www. physionet. org. The results showed that compared to traditional moving average filter and wavelet package (WP) translation, the proposed filter could more effectively correct baseline in ECG signal and result in less distortion to ECG signal.