脉搏信号中运动伪差噪声的消除

The Elimination of Movement Artifact in Pulse Signals

低信噪比中信号的提取是生物医学信号提取的难点,运动伪差噪声的消除更是瓶颈。本文针对这种运动伪差噪声提出一种新的解决方法。根据脉搏信号的特征,首先对信号进行小波分解,再对有用信号频段内的小波系数进行经验模态分解(EMD),从而有效的将有用信号和低频运动噪声区分开。然后,分别从信噪比、能量比、互相关系数和频谱等方面验证所提出方法的有效性;利用此方法,不但去掉了运动伪差噪声,同时去掉了基线漂移和高频噪声,为计算脉率和血氧饱和度提供了有效的途径。

It is difficult to extract signals under Low Signal Noise Ratio in biomedical signal processing. The elimination of movement artifact is really a bottleneck. A new solution for the movement artifact in pulse signal is proposed in this paper. According to pulse signal features,the signal is decomposed by using wavelet transform firstly. Then empirical mode decomposition （EMD） is applied to the wavelet coefficients in frequency band of useful signals,thus the signal and movement artifact can be distinguished effectively. Furthermore,the effectiveness of the proposed approach is verified by signal-to-noise ratio,energy ratio,cross correlation coefficient and power spectrum. This method can eliminate not only movement artifact,but also baseline wander and high-frequency noise. Thus,it provides an effective approach for the calculation of pulse rate and blood oxygen saturation.