摘要
非接触测量是实现对人体心电(ECG)信号长时间监测的一种有效方法。由于测量电极与人体之间的相对位置不固定,导致采集的ECG信号不断的发生变化,在滤波时经常出现ECG信号被削弱而失真的情况。本文运用主成分分析(PCA)的基础理论,提出了一种快速自适应PCA去噪算法,该算法能够根据ECG信号的改变自动的调整参数。通过实验证明了PCA去噪算法几乎不受信号变化的影响,能够在保留ECG信号主要特征的前提下将干扰信号一次性去除,同时很好的解决了ECG信号在滤波时被削弱的问题。
Non-contact measurement is an effective method of long time measurement of human electrocardiograph （ECG） signal. Because the relative position between measuring electrode and human body is not fixed, this method could result in constant changes of ECG signal collection. It often appears ECG signal distorting and weakened in fil- tering. This paper, using the principal component analysis （PCA） basic theory, proposes a fast adaptive PCA de- noising algorithm which can automatically adjust the parameters according to the changes of ECG signal. The experi- ment proved that PCA denoising could be barely impacted by signal changes and can disposably remove interference signal on the premise of keeping the main features of ECG signal and can prevent ECG signal from being weakened in filtering at the same time.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2013年第3期499-502,共4页
Journal of Biomedical Engineering
关键词
耦合电容
主成分分析
动态嵌入
幅值特性
Coupling capacitance
Principal component analysis （PCA）
Dynamical embedding （DE）
Amplitude characteristic
