Liu Baohua, Zhen Long, Hu Pengfei
College of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2013 Jun;30(3):499-502.
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 filtering. This paper, using the principal component analysis (PCA) basic theory, proposes a fast adaptive PCA denoising algorithm which can automatically adjust the parameters according to the changes of ECG signal. The experiment 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.
非接触测量是长时间测量人体心电图（ECG）信号的一种有效方法。由于测量电极与人体之间的相对位置不固定，这种方法可能导致心电图信号采集的不断变化。在滤波过程中，经常会出现心电图信号失真和减弱的情况。本文利用主成分分析（PCA）基本理论，提出了一种快速自适应PCA去噪算法，该算法可以根据心电图信号的变化自动调整参数。实验证明，PCA去噪受信号变化的影响很小，能够在保留心电图信号主要特征的前提下一次性去除干扰信号，同时还能防止心电图信号在滤波过程中被减弱。
