Ecg Denoising
Kurtosis based Multichannel ECG Signal Denoising and Diagnostic Distortion Measures
Sharma L. N.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: lns@iitg.ernet.in
Dandapat S.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: samaren@iitg.ernet.in
Mahanta A.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: anilm@iitg.ernet.in
Abstract—Multichannel Electrocardiogram (MECG) signal denoising can be described as a process of removing the clinically unimportant contents present from the signal. Higher Order Statistics (HOS) can help to retain finer details of an Electrocardiogram (ECG) signal which can effectively reduce the noise levels in MECG signal. In this work, it is proposed to evaluate the HOS (Kurtosis) in each Wavelet band to denoise an MECG signal. Thresholding levels are derived based on the values of fourth order cumulant, ‘Kurtosis’, of the Wavelet coefficients and Energy Contribution Efficiency (ECE) of Wavelet sub-bands. The performance of this method for compressed signals is evaluated using Percentage Root Mean Square Difference (PRD), Weighted PRD (WPRD), and Wavelet Weighted Percentage Root Mean Square Difference (WWPRD). The proposed algorithm is tested with database of CSE Mutlilead Measurement Library. The results show significant improvement in denoising the MECG signals.
I. I NTRODUCTION According to the published literature, majority of the signal denoising methods in the Wavelet domain are based on soft and hard thresholding. The noisy signal is decomposed up to a suitable level, j, using Discrete Wavelet Transform (DWT) and based on noise variance Wavelet coefficients are thresholded √ at t = σ 2 log N (where t is threshold, σ is variance of noise and N is the numbers of samples) [1], [2]. It is
Sharma L. N.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: lns@iitg.ernet.in
Dandapat S.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: samaren@iitg.ernet.in
Mahanta A.
Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati, India - 781 039 Email: anilm@iitg.ernet.in
Abstract—Multichannel Electrocardiogram (MECG) signal denoising can be described as a process of removing the clinically unimportant contents present from the signal. Higher Order Statistics (HOS) can help to retain finer details of an Electrocardiogram (ECG) signal which can effectively reduce the noise levels in MECG signal. In this work, it is proposed to evaluate the HOS (Kurtosis) in each Wavelet band to denoise an MECG signal. Thresholding levels are derived based on the values of fourth order cumulant, ‘Kurtosis’, of the Wavelet coefficients and Energy Contribution Efficiency (ECE) of Wavelet sub-bands. The performance of this method for compressed signals is evaluated using Percentage Root Mean Square Difference (PRD), Weighted PRD (WPRD), and Wavelet Weighted Percentage Root Mean Square Difference (WWPRD). The proposed algorithm is tested with database of CSE Mutlilead Measurement Library. The results show significant improvement in denoising the MECG signals.
I. I NTRODUCTION According to the published literature, majority of the signal denoising methods in the Wavelet domain are based on soft and hard thresholding. The noisy signal is decomposed up to a suitable level, j, using Discrete Wavelet Transform (DWT) and based on noise variance Wavelet coefficients are thresholded √ at t = σ 2 log N (where t is threshold, σ is variance of noise and N is the numbers of samples) [1], [2]. It is