Research Centre of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
J Healthc Eng. 2020 Jul 29;2020:8868685. doi: 10.1155/2020/8868685. eCollection 2020.
R-wave detection is a prerequisite for the extraction and recognition of ECG signal feature parameters. In the analysis and diagnosis of exercise electrocardiograms, accurate and real-time detection of QRS complexes is very important for the prevention and monitoring of heart disease. This paper proposes a lightweight R-wave real-time detection method for exercise ECG signals. After real-time denoising of the exercise ECG signal, the median line is used to correct the baseline, and the first-order difference processing is performed on the differential square signal. Max-Min Threshold (MMT) is used to realize real-time R-wave detection of the exercise ECG signal. The abovementioned method was verified by using the measured data in the MIT-BIH ECG database of the Massachusetts Institute of Technology and the exercise plate experiment. The R-wave detection rates were 99.93% and 99.98%, respectively. Experimental results show that this method has high accuracy and low computational complexity and is suitable for wearable devices and motion process monitoring.
R 波检测是提取和识别 ECG 信号特征参数的前提。在运动心电图的分析和诊断中，准确、实时地检测 QRS 波群对于心脏病的预防和监测非常重要。本文提出了一种用于运动 ECG 信号的轻量级 R 波实时检测方法。对运动 ECG 信号进行实时去噪后，使用中线校正基线，并对差分平方信号进行一阶差分处理。使用最大-最小阈值（MMT）实现运动 ECG 信号的实时 R 波检测。上述方法分别使用麻省理工学院的麻省理工学院-比奇（MIT-BIH）心电图数据库中的实测数据和运动平板实验进行了验证。R 波检测率分别为 99.93%和 99.98%。实验结果表明，该方法具有较高的准确性和较低的计算复杂度，适用于可穿戴设备和运动过程监测。
