ECG Denoising based on PCA and using R Peaks Detection

Talbi Mourad

Abstract

In this paper, we propose a new Electrocardiogram (ECG) Denoising technique based on Principal Component Analysis (PCA) and using R peaks detection. This technique consists at first step in cutting the entire ECG signal into frames then the denoising is performed frame by frame by using PCA. Each frame is located between two successive R peaks. The R peaks detection is performed by using a new detection method based on multi-scale product of the undecimated wavelet coefficients. The Reconstructed ECG signal is obtained by concatenating all the denoised frames. The evaluation of the proposed technique is performed by comparing it to the denoising technique based on PCA and applied to the entire noisy ECG signal. The two techniques are tested on four ECG signals taken from MIT-BIH database. The used criteria in this evaluation of these two techniques are the SNR improvement and the mean square error (MSE). The obtained results from this evaluation show clearly that the denoising technique based on PCA and applied to the entire noisy ECG signal, is slightly better than the proposed technique. However this latter has the advantage of working in real-time because the processing is performed frame by frame and not on the entire noisy ECG signal. Concerning the new proposed technique of R peaks detection, it is very accurate because it permits a perfect reconstruction of the ECG signal when concatenating all the frames.

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Paper Citation


in Harvard Style

Mourad T. (2015). ECG Denoising based on PCA and using R Peaks Detection . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 119-125. DOI: 10.5220/0004998201190125


in Bibtex Style

@conference{biosignals15,
author={Talbi Mourad},
title={ECG Denoising based on PCA and using R Peaks Detection},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={119-125},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004998201190125},
isbn={978-989-758-069-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - ECG Denoising based on PCA and using R Peaks Detection
SN - 978-989-758-069-7
AU - Mourad T.
PY - 2015
SP - 119
EP - 125
DO - 10.5220/0004998201190125