Débruitage des sigunaux ECG a l aide du seuillage adaptatif par ondelettes et du filtrage de wiener.

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dc.contributor.authorAISSAOUI, RANIM
dc.date.accessioned2026-09-29T10:15:51Z
dc.date.available2026-09-29T10:15:51Z
dc.date.issued2026
dc.description.abstractElectrocardiogram (ECG) signal recording is a challenging task in the field of biomedical engineering. ECG is the cardiac recording of the systemic electrical activity arising from the electro-physiological rhythm of the heart muscle. However, during processing, the ECG signal is contaminated by various types of noise in the medical environment. An immense task is the separation of the preferred signal from noise caused by additive AWGN, artifacts such as muscle noise, power line interference (PLI), baseline wandering (BW), and motion artifacts (MA). In this work, the effectiveness of the Discrete Wavelet Transform (DWT) combined with the Wiener filter for denoising ECG signals corrupted by AWGN and baseline wandering (BW) is investigated. Real and synthetic ECG data from the MIT-BIH database are used in experiments to demonstrate the approach’s effectiveness for ECG denoising. The results indicate that the approach improves the signal-to-noise ratio (SNR) and MSE, as also confirmed by visual inspection of the records. Our method offers clear advantages, particularly in preserving detailed information on the QRS complex of the ECG, which is significant for feature extraction of ECG signals and for pathological diagnosis.
dc.identifier.urihttp://dspace.univ-khenchela.dz:4000/handle/123456789/11543
dc.language.isoen
dc.titleDébruitage des sigunaux ECG a l aide du seuillage adaptatif par ondelettes et du filtrage de wiener.
dc.typeThesis
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