Key result
MCBSR module outperforms conventional methods in QRS detection and noise robustness.
Why the study?
Inevitable noise in ECG signals deteriorates QRS detection performance, and existing monostable stochastic resonance algorithms exhibit a limited noise margin.
A novel multi-parameter constrained bistable stochastic resonance module improves QRS detection and noise robustness in ECG signals compared to conventional nonlinear methods.
May enhance QRS detection in noisy ECGs; leaves open prospective validation before clinical use.
One major challenge of QRS wave detection is the deleterious impact of inevitable noise in electrocardiogram (ECG) signals, which can deteriorate the detection performance of algorithms. Previous research has shown a nonlinear monostable potential‐based algorithm for enhancing the QRS complex in a noisy environment. Its main mechanism is the stochastic resonance effect, which transfers noise energy to information‐carrying ECG signals in the nonlinear potential. However, the QRS detection algorithm based on monostable stochastic resonance (MSR) exhibits a limited noise margin to maintain extremely good performance. To further improve noise robustness, we propose a multi‐parameter constrained bistable SR (MCBSR) module for the QRS detection algorithm without requiring a large amount of training data. The MCBSR module can maximize the ECG signal while suppressing noise when there is a QRS complex and minimizes the ECG signal otherwise. Using four publicly available databases for testing, the MCBSR‐based QRS detection algorithm has been proven to achieve superior performance among state‐of‐the‐art algorithms. Compared to the conventional nonlinear method, the MCBSR enables the QRS detection algorithm to have significantly stronger noise robustness under various noise types. Therefore, this study successfully provides a more excellent nonlinear potential and greatly enhances the noise robustness of the QRS detection algorithm in large noise environments.
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Shang et al. (2025) studied Noisy electrocardiogram (ECG) signals. Multi-parameter constrained bistable stochastic resonance (MCBSR) module vs. Conventional nonlinear method (monostable stochastic resonance) was evaluated on QRS detection performance and noise robustness. The multi-parameter constrained bistable stochastic resonance (MCBSR) module achieved superior QRS detection performance and significantly stronger noise robustness compared to conventional methods.
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