Electronics, Communication & Automation Technology

A Feed-Forward Combined Adaptive Filter for Suppressing Motion Artifact in Ambulatory Electrocardiogram

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  • 1.Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,Shanghai 200050,China; 2.University of Chinese Academy of Sciences,Beijing 100049,China; 3.Central Hospital of Xuhui District,Shanghai 200031,China
张洹千(1983-),男,博士生,主要从事生物传感器研制研究. E-mail:huanqian.zhang@mail.sim.ac.cn

Received date: 2017-02-17

  Revised date: 2017-04-19

  Online published: 2017-10-31

Supported by

 Supported by the Foundation of Shanghai Municipal Science and Technology Commission(14521106200)

Abstract

The least mean square adaptive filter (LMS-AF) and the variable step size LMS-AF (VSS-LMS-AF) have been widely used to suppress the motion artifact (MA) from ambulatory electrocardiograms (AECG).How- ever,due to the fact that the non-stationary property of the MA and the AECG increases the mis-adjustment of fil- ters,although the combined AF (C-AF) has advantages in tracking non-stationary signals,it still suffers from a signal distortion.In order to further decrease the signal distortion and improve the MA suppression ability,a new feed-forward combined AF (FFC-AF) is proposed,in which the stationary degree of the MA is estimated by using a reference signal and two parallel AF outputs are combined.Then,a simulation experiment with the AECG re- cording on ten healthy volunteers is conducted to assess the performance of the FFC-AF.The results show that,as compared with the C-AF,the FFC-AF is of less signal distortion and larger signal artifact ratio.Therefore,it can be used to suppress the MA in the AECG.

Cite this article

ZHANG Huan-qian ZHANG Shu-lin DU Xiao-wei JIN Qing-hui LI Qing YANG Jian ZHAO Jian-long . A Feed-Forward Combined Adaptive Filter for Suppressing Motion Artifact in Ambulatory Electrocardiogram[J]. Journal of South China University of Technology(Natural Science), 2017 , 45(12) : 65 -70 . DOI: 10.3969/j.issn.1000-565X.2017.12.010

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