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The research evaluates how integrating discrete wavelet transform (DWT) with adaptive filters (A-F) enhances the reduction of electrocardiogram (ECG) signal noise. The correct interpretation of heart... diseases through ECG signals depends heavily on signal quality because multiple noise types can affect the signals. Powerline interference (PLI) together with motion artifacts (MA) and baseline wander (BW) and electromyogram (EMG) interference constitute the noise sources affecting electrocardiogram (ECG) signals. This interference can either be correlated or uncorrelated. Noises must be eliminated because they create diagnostic inaccuracy and unreliability. The study develops an AF-WT- based filter system to solve this issue. This research evaluates the DWT and A-F based filter against standard DWT and A-F for signal processing. The DWT and A-F besd filter produces an acceptable signal to noise ration (SNR) while simultaneously removing all major ECG signal distortions including PLI, MA, BW and EMG noise thus showing promise for diagnostic accuracy enhancement.続きを見る
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Mendeley出力
2025_p0331