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

  • Shumei Dai
  • Dongyi ChenEmail author
  • Fan Xiong
  • Zhenghao Chen
Conference paper
  • 40 Downloads
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

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.

Keywords

ECG SPV Motion artifacts Textile electrodes 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Shumei Dai
    • 1
  • Dongyi Chen
    • 1
    Email author
  • Fan Xiong
    • 1
  • Zhenghao Chen
    • 1
  1. 1.University of Electronic Science and Technology of China, School of Automation EngineeringChengduChina

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