Title: Hardware implementation of ECG denoising system using TMS320C6713 DSP processor

Authors: S.A. Anapagamini; R. Rajavel

Addresses: Department of Electronics and Communication Engineering, SSN College of Engineering, Rajiv Gandhi Salai (OMR), Chennai 603110, India ' Department of Electronics and Communication Engineering, SSN College of Engineering, Rajiv Gandhi Salai (OMR), Chennai 603110, India

Abstract: The electrocardiogram (ECG) signal is an extensively used biomedical signal for diagnosis of heart diseases. However, the quality of ECG signal is deteriorated by several noises during its acquisition. The two dominant and recurring noises are power line interference and baseline wander noise and they have to be removed for better clinical evaluation. This paper proposes a new ECG denoising system using a combination of Empirical Mode Decomposition (EMD) algorithm and FFT-based frequency analysis. The proposed ECG denoising system is first simulated and validated using MATLAB. Then, it is implemented in TMS320C6713 DSP processor using Code Composer Studio (CCS). The proposed system is tested with the standard ECG signals obtained from Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database. The root mean square error (RMSE) and correlation coefficient are used as the evaluation measure to compare the performance of the proposed method with an existing denoising system. The experimental results with reduced RMSE value and the average correlation coefficient of 0.9889 between the original ECG and the denoised one indicate the successful removal of power line interference and baseline wander noise by the proposed ECG denoising system.

Keywords: ECG signals; signal denoising; ECG denoising; powerline interference; empirical mode decomposition; EMD; baseline wander noise; FFT analysis; fast Fourier transform; hardware implementation; DSP processors; digital signal processing; electrocardiograms; biomedical signals; diagnosis; heart disease; simulation; cardiovascular disease; root mean square error; RMSE; correlation coefficient.

DOI: 10.1504/IJBET.2016.076735

International Journal of Biomedical Engineering and Technology, 2016 Vol.21 No.1, pp.95 - 108

Received: 04 Jun 2015
Accepted: 19 Oct 2015
Published online: 24 May 2016 *

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