Journal of Electromyography and Kinesiology
Volume 20, Issue 3 , Pages 542-549, June 2010

A wavelet-based adaptive filter for removing ECG interference in EMGdi signals

  • Choujun Zhan

      Affiliations

    • Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
    • ,
  • Lam Fat Yeung

      Affiliations

    • Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
    • Corresponding Author InformationCorresponding author.
    • ,
  • Zhi Yang

      Affiliations

    • School of Information Science and Technology, Sun Yat-Sen University, Guang Zhou, China

Received 23 March 2009; received in revised form 27 May 2009; accepted 22 July 2009. published online 19 August 2009.

Abstract 

Diaphragmatic electromyogram (EMGdi) signals convey important information on respiratory diseases. In this paper, an adaptive filter for removing the electrocardiographic (ECG) interference in EMGdi signals based on wavelet theory is proposed. Power spectrum analysis was performed to evaluate the proposed method. Simulation results show that the power spectral density (PSD) of the extracted EMGdi signal from an ECG corrupted signal is within 1.92% average error relative to the original EMGdi signal. Testing on clinical EMGdi data confirm that this method is also efficient in removing ECG artifacts from the corrupted clinical EMGdi signal.

Keywords: EMGdi, ECG, Wavelet, Adaptive filter

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PII: S1050-6411(09)00099-6

doi:10.1016/j.jelekin.2009.07.007

Journal of Electromyography and Kinesiology
Volume 20, Issue 3 , Pages 542-549, June 2010

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