Motion Artifact Reduction in Electrocardiogram Using Adaptive Filtering Based on Skin-Potential Variation Monitoring

Wearable devices which measure electrocardiogram (ECG) for continuous and real-time health monitoring become increasingly popular; ECG signals measured by textile electrodes in wearable devices can be easily disturbed by motion artifacts, which can cause misdiagnoses, leading to inappropriate treatment decisions. In this study, a simple method was demonstrated to measure skin-potential variation (SPV). SPV signals were obtained by two additional textile electrodes, which were positioned adjacent to the ECG sensing electrodes and connected with a resistance. Motion artifacts are adaptively filtered by using SPV as the reference variable. The results demonstrate that this device and method can significantly reduce skin-potential variation induced ECG artifacts.