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Efficacy of DWT denoising in the removal of power line interference and the effect on morphological distortion of underlying atrial fibrillatory waves in AF-ECG.

Goodfellow, J, Escalona, OJ, Kodoth, V and Manoharan, G (2015) Efficacy of DWT denoising in the removal of power line interference and the effect on morphological distortion of underlying atrial fibrillatory waves in AF-ECG. In: World Congress on Medical Physics and Biomedical Engineering -2015, Toronto, Canada.. Springer International Publishing, Switzerland. Vol 51 4 pp. [Conference contribution]

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URL: http://link.springer.com/chapter/10.1007%2F978-3-319-19387-8_257

DOI: 10.1007/978-3-319-19387-8_257

Abstract

The objective of this study is to assess the efficacy of Discrete Wavelet Transform (DWT) in the removal of power line (50Hz) interference (PLI). Eighteen mains noise corrupted ECG signals were denoised using thirty two different DWT mother wavelets in order to assess which are the top performing for power line interference cancellation. For comparative purposes the signals were also denoised using a traditional notch filtering approach and the results assessed using three performance parameters: Signal to noise ratio (SNR), Mean Square Error (MSE) and Signal Correlation Value (SCV). 12 of the 32 wavelet functions utilized for mains interference denoising outperformed the traditional notch filtering approach, with the top four performing wavelets being Daubechies ‘Db10’, Biorthogonal ‘Bior6.8’, DMeyer ‘Dmey’ and Daubechies ‘Db8’, with Db10 producing SNR, MSE and CCV values of 32.50, 5.13x10− 5 and 0.9995 respectively. This was considerably better than the notch filtering technique which produced comparable results of 25.67, 1.10x10− 3 and 0.9952 respectively. The second phase of this study assessed the effect that DWT PLI attenuation had on underlying fibrillatory wave morphology. The results indicate that discrete wavelet processing has a negligible effect on underlying fibrillatory waves and is therefore a viable method for mains noise removal in ECG analysis of AF patients.

Item Type:Conference contribution (Paper)
Keywords:Wavelet Transform, DWT, atrial fibrillation, AF–ECG, 50Hz Interference removal, ECG denoising.
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
ID Code:32805
Deposited By: Professor Omar Escalona
Deposited On:11 Jan 2016 09:29
Last Modified:11 Jan 2016 09:29

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