Key result
Denoising ECG signals using the Framelet transform with median-based thresholding was proposed and its performance evaluated against the wavelet transform.
Framelet transform with median-based soft thresholding provides superior ECG signal denoising (higher SNR) compared to traditional wavelet transform methods.
May advance ECG denoising in computational research; leaves open clinical validation and diagnostic impact.
Denoising of the ECG signals is required, as they are prone to noises during their acquisition. Currently, denoising techniques for ECG signals are mostly available in the wavelet transform domain. In this paper, an approach for denoising the ECG signals in the Framelet domain is proposed. Initially, signals are decomposed using the Framelet transform. After decomposition, they are denoised using a median based thresholding method. The performance evaluation is carried out by comparing the results with that of the wavelet transform.
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Cyriac et al. (2014) studied ECG signal noise. Framelet Transform vs. Wavelet transform was evaluated on Denoising performance. Denoising ECG signals using the Framelet transform with median-based thresholding was proposed and its performance evaluated against the wavelet transform.
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