Key result
The enhanced discrete wavelet transform method achieved a 1-5 dB signal-to-noise ratio improvement for Gaussian white noise compared to traditional DWT.
Why the study?
Achieving accurate and real-time monitoring of heartbeat signals using non-invasive sensing techniques is challenging because of various noise interferences.
Effect estimate: 1-5 dB SNR improvement
An enhanced DWT method significantly improves the signal-to-noise ratio of non-invasive heartbeat signals, potentially increasing diagnostic accuracy.
Could aid accurate non-invasive ECG monitoring; leaves open clinical validation before practice adoption.
Achieving both accurate and real-time monitoring heartbeat signals by non-invasive sensing techniques is challenging due to various noise interferences. In this paper, we propose an enhanced discrete wavelet transform (DWT) method that incorporates objective denoising quality assessment metrics to determine accurate thresholds and adaptive threshold functions. Our approach begins by denoising ECG signals from various databases, introducing several types of typical noise, including additive white Gaussian (AWG) noise, baseline wandering noise, electrode motion noise, and muscle artifacts. The results show that for Gaussian white noise denoising, the enhanced DWT can achieve 1-5 dB SNR improvement compared to the traditional DWT method, while for real noise denoising, our proposed method improves the SNR tens or even hundreds of times that of the state-of-the-art denoising techniques. Furthermore, we validate the effectiveness of the enhanced DWT method by visualizing and comparing the denoising results of heartbeat signals monitored by fiber-optic micro-vibration sensors against those obtained using other denoising methods. The improved DWT enhances the quality of heartbeat signals from non-invasive sensors, thereby increasing the accuracy of cardiovascular disease diagnosis.
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Zhu et al. (2025) studied Heartbeat signal denoising. Enhanced discrete wavelet transform (DWT) method vs. Traditional DWT method and state-of-the-art denoising techniques was evaluated on Signal-to-noise ratio (SNR) improvement (1-5 dB SNR improvement). The enhanced discrete wavelet transform method achieved a 1-5 dB signal-to-noise ratio improvement for Gaussian white noise compared to traditional DWT.
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