A Stochastic Resonance P- and T-wave Detection Algorithm
A Stochastic Resonance P- and T-wave Detection Algorithm
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DOI：
10.1109/embc48229.2022.9871435
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
C. Güngör;P. Mercier;H. Töreyin
中科院分区：
文献类型：
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作者：
C. Güngör;P. Mercier;H. Töreyin
提出了一种检测心电图（ECG）信号中P波和T波的算法。该算法的物理起源的启发，弱信号检测利用随机共振（SR）在一个良好的潜力。具体而言，欠阻尼单稳态阱内的粒子与ECG信号一起引入。定义井和系统特性的参数被优化以增强P波、R波和T波，同时抑制包括仅噪声部分的其它部分。通过阈值化检测增强的特征。基于从QT数据库获得的性能，该算法实现了P波的平均灵敏度为99.97%，T波的平均灵敏度为99.35%，优于大多数P波和T波检测算法。临床相关性-所提出的SR算法实现了较高的P波和T波检测性能，并且可能与植入式长期心脏监护仪集成，用于出现罕见症状的患者，而不会降低电池寿命。
An algorithm to detect P- and T-waves in an electrocardiogram (ECG) signal is presented. The algorithm has physical origins inspired by weak signal detection by leveraging stochastic resonance (SR) in a well potential. Specifically, a particle inside an underdamped monostable well is introduced with the ECG signal. The parameters defining the well and system characteristics are optimized towards enhancing the P-, R-, and T -waves while suppressing the other portions including noise-only sections. The enhanced features are detected by thresholding. Based on the performance obtained from the QT database, the algorithm achieves an average sensitivity of 99.97% for P-waves and an average sensitivity of 99.35% for T-waves, better than most P- and T-wave detection algorithms reported. Clinical Relevance— The proposed SR algorithm achieves high P- and T-wave detection performance and can potentially be integrated with implantable long-term cardiac monitors for patients experiencing rare symptoms without deteriorating the battery life.