ECG Signal De-Noising with Asynchronous Averaging and Filtering Algorithm

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Author(s): Alka Gautam (Dongseo University, Korea), Hoon-Jae Lee (Dongseo University, Korea)and Wan-Young Chung (Pukyong National University, Korea)
Copyright: 2012
Pages: 7
Source title: Advancing Technologies and Intelligence in Healthcare and Clinical Environments Breakthroughs
Source Author(s)/Editor(s): Joseph Tan (McMaster University, Canada)
DOI: 10.4018/978-1-4666-1755-1.ch014

Keywords: Health Information Systems / Medical Information Science Reference / Medicine & Healthcare

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Abstract

In this study, a new algorithm is proposed—Asynchronous Averaging and Filtering (AAF) for ECG signal de-noising. R-peaks are detected with another proposed algorithm—Minimum Slot and Maximum Point selecting method (MSMP). AAF algorithm reduces random noise (major component of EMG noise) from ECG signal and provides comparatively good results for baseline wander noise cancellation. Signal to noise ratio (SNR) improves in filtered ECG signal, while signal shape remains undistorted. The authors conclude that R-peak detection with MSMP method gives comparable results from existing algorithm like Pan-Tomkins algorithm. AAF algorithm is advantageous over adaptation algorithms like Wiener and LMS algorithm. Overall performance of proposed algorithms is comparatively good.

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ECG Signal De-Noising with Asynchronous Averaging and Filtering Algorithm

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