ECG Signal Denoising by Discrete Wavelet Transform
Autor: | Mounaim Aqil, Abdennasser Bourouhou, Atman Jbari |
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Rok vydání: | 2017 |
Předmět: |
0301 basic medicine
Discrete wavelet transform Engineering Mean squared error business.industry Noise (signal processing) Noise reduction Second-generation wavelet transform General Engineering Pattern recognition 02 engineering and technology Function (mathematics) Signal 03 medical and health sciences 030104 developmental biology Wavelet Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business |
Zdroj: | International Journal of Online Engineering (iJOE). 13:51 |
ISSN: | 1861-2121 1868-1646 |
Popis: | The denoising of electrocardiogram (ECG) represents the entry point for the processing of this signal. The widely algorithms for ECG denoising are based on discrete wavelet transform (DWT). In the other side the performances of denoising process considerably influence the operations that follow. These performances are quantified by some ratios such as the output signal on noise (SNR) and the mean square error (MSE) ratio. This is why the optimal selection of denoising parameters is strongly recommended. The aim of this work is to define the optimal wavelet function to use in DWT decomposition for a specific case of ECG denoising. The choice of the appropriate threshold method giving the best performances is also presented in this work. Finally the criterion of selection of levels in which the DWT decomposition must be performed is carried on this paper. This study is applied on the electromyography (EMG), baseline drift and power line interference (PLI) noises. |
Databáze: | OpenAIRE |
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