Abstract
Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to remove motion artefact superimposed on ECG signal when using non-contact capacitively coupling electrodes. The authors evaluate the effect on motion artefact removal of this algorithm by applying it to various ECG signals with motion artefacts superimposed. As a result, the correlation coefficients of ECG signals with respect to the clean ones have been improved from 0.71 to 0.88 on median before and after motion artefact removal, which demonstrates the validity of the proposed SWT-based algorithm.
Highlights
In recent years, the demand on information and communication technology is increasing in healthcare and medical applications
A quantitative evaluation was conducted by calculating the correlation coefficients between the ECG signal after motion artefact removal and the clean ECG signal
Wearable ECG integrated with non-contact ECG detection and human body communication can provide a lot of convenience in daily monitoring of ECG signal
Summary
The demand on information and communication technology is increasing in healthcare and medical applications. This wearable ECG employs human body as the communication medium and the detected ECG signal can be send to a receiver when the human hand touches it For non-contact electrode structure of ECG detection, an accelerometer directly attached to the human body is unacceptable Another attempt is to employ stationary wavelet transform (SWT) to remove the motion artefact [6], where the QRS complex is extracted based on the energy of ECG signal. We verify its validity in motion artefact removal by applying it to various ECG signals with superimposed body movement effect
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