Motion artifact removal for wearable ECG using stationary wavelet multi-resolution analysis

Abstract

Wearable electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the view-point of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, we propose an algorithm using the stationary wavelet transform (SWT) to remove motion artifact superimposed on ECG signal when using non-contact capacitively coupling electrodes. In addition, we confirmed that the proposed algorithm performed well on the ECG signals including a premature ventricular contraction (PVC) using MIT-BIH Arrhythmia Database. As a result, the correlation coefficients of ECG signals with respect to the clean ones have been improved from 0.61 to 0.84 on median before and after motion artifact removal, which demonstrates the validity of the proposed SWT-based algorithm.