心脏心冲击信号降噪方法研究

De-noising Method Research of Ballistocardiogram Signal

心冲击(BCG)信号是反映心脏机械运动的生理信号,测量中无需在受试者身体表面贴附电极,能实现无感觉生理监护。但BCG信号微弱,易受到干扰,测量时经常被淹没在噪声中。为了有效识别BCG信号,提出一种基于时频联合分布和经验模态分解(EMD)的BCG信号降噪方法。该方法先建立BCG信号的自适应最优核,然后在时频平面内提取BCG信号分量,最后根据EMD原理对BCG信号分量进行滤波,从而实现BCG信号降噪。仿真研究表明,该方法克服了EMD处理在不同时间含有相同或相似频率成分信号时的不足,所提出方法实现了BCG信号降噪,可以有效还原BCG信号特征。

Ballistocardiogram （BCG） signal is a physiological signal, reflecting heart mechanical status. It can be measured without any electrodes touching subject＇s body surface and can realize physiological monitoring ubiquitous- ly. However, BCG signal is so weak that it would often be interferred by superimposed noises. For measuring BCG signal effectively, we proposed an approach using joint time-frequency distribution and empirical mode decomposition （EMD） for BCG signal de-noising. We set up an adaptive optimal kernel for BCG signal and extracted BCG signals components using it. Then we de-noised the BCG signal by combing empirical mode decomposition with it. Simula- tion results showed that the proposed method overcome the shortcomings of empirical mode decomposition for the signals with identical frequency content at different times, realized the filtering for BCG signal and also reconstructed the characteristics of BCG.