基于改进差分阈值算法的心电检测技术研究

针对差分阈值算法中固定阈值的局限性,文中提出了一种基于自适应波峰阈值和R波间隔阈值的算法。该算法结合心电信号特点自动选择波峰阈值,并选择R波间隔阈值,提高了算法的自适应性和准确率。文中以MIT-BIH心律失常数据库中的心电信号作为实验样本,采用带通滤波与小波阈值滤波相结合的方法完成心电信号去噪,采用改进差分自适应阈值算法对心电信号进行波形检测。实验结果表明,该算法能够将心电信号R波的检测准确率提升到99.57%,有效减少了误检、漏检问题的发生,并可准确完成心率、心率变异性、身体疲劳度、精神疲劳度计算和常见心律失常分类。

Research of ECG Detection Technology Based on Improved Differential Threshold Algorithm

Aiming at the limitation of fixed threshold in differential threshold algorithm, an algorithm based on adaptive peak threshold and R wave interval threshold was proposed. The algorithm automatically selected the peak threshold based on the characteristics of the ECG signal, and selected the R-wave interval threshold to improve the adaptability and accuracy of the algorithm. In this study, the ECG signal in the MIT-BIH arrhythmia database was used as the experimental sample. The combination of bandpass filtering and wavelet threshold filtering were utilized to complete the denoising of ECG signals. The ECG signals were detected by the improved differential adaptive threshold algorithm. The experimental results showed that the algorithm could improve the detection accuracy of R wave of ECG signal to 99.57%. The algorithm effectively reduced the occurrence of false detections and missed inspections, and accurately calculated heart rate, heart rate variability, physical fatigue, mental fatigue and common arrhythmia classification.