Abstract
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.
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Acknowledgments
This work is supported by National Natural Science Foundation of China (no. 61572110) and National Key Research & Development Plan of China (no. 2016YFB1001401).
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Dai, S., Chen, D., Xiong, F., Chen, Z. (2020). Motion Artifact Reduction in Electrocardiogram Using Adaptive Filtering Based on Skin-Potential Variation Monitoring. In: Sugimoto, C., Farhadi, H., Hämäläinen, M. (eds) 13th EAI International Conference on Body Area Networks . BODYNETS 2018. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-29897-5_41
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DOI: https://doi.org/10.1007/978-3-030-29897-5_41
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