Why the study?
Achieving heightened accuracy in denoising ECG signals to enhance feature extraction remains an enduring challenge in diagnosing heart disease.
Does a weighted iterative UFIR filter improve ECG signal denoising compared to a Savitzky-Golay filter?
Does a weighted iterative UFIR filter improve ECG signal denoising compared to a Savitzky-Golay filter?
The weighted iterative UFIR filter provides superior ECG signal denoising with lower error and higher signal-to-noise ratio compared to traditional Savitzky-Golay filters.
Weighted UFIR filter may aid ECG denoising; leaves open clinical utility pending validation.
The electrocardiogram (ECG) holds paramount importance in diagnosing heart disease, and as it persists leading cause of global mortality. Over the past decades, diverse techniques have emerged for processing ECG signals, with denoising taking a prominent role in enhancing feature extraction. Nonetheless, achieving heightened accuracy remains an enduring challenge. In this study, we introduce an innovative approach involving the application of a weighted unbiased finite impulse response (UFIR) filter. Under the same noise conditions and in terms of the root mean square error (RMSE) and signal-to-noise ratio (SNR), our proposed method showcases worthy performance in comparison to the weighted Savitzky-Golay (SG) filter. This research contributes to the progressive evolution of ECG signal processing, offering the potential for more precise and dependable detection of cardiac diseases.
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Lastre-Domínguez et al. (2023) studied this question.
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