Exercise Fatigue Monitoring Based on R-Peak Detection Using UNET-TCN  

作　　者：Xinhua Su Xuxuan Wang Xinxin Ma 

机构地区：[1]Schoolof Sports Engineering,Beijing Sport University,Beijing100091,China

出　　处：《Journal of Beijing Institute of Technology》2024年第4期337-345,共9页北京理工大学学报（英文版）

基　　金：the National Natural Science Foundation of China(No.62301056);the Fundamental Research Funds for Central Universities(No.2022QN005).

摘　　要：Moderate exercise contributes to health, but excessive exercise may lead to physicalinjury or even endanger life. It is pressing for a device that can detect the intensity of exercise.Therefore, in order to enable real-time detection of exercise intensity and mitigate the risks of harmfrom excessive exercise, a exercise intensity monitoring system based on the heart rate variability(HRV) from electrocardiogram (ECG) signal and linear features from phonocardiogram (PCG)signal is proposed. The main contributions include: First, accurate analysis of HRV is crucial forsubsequent exercise intensity detection. To enhance HRV analysis, we propose an R-peak detectorbased on encoder-decoder and temporal convolutional network (TCN). Experimental resultsdemonstrate that the proposed R-peak detector achieves an F1 score exceeding 0.99 on real high-intensity exercise ECG datasets. Second, an exercise fatigue monitoring system based on multi-signal feature fusion is proposed. Initially, utilizing the proposed R-peak detector for HRV extractionin exercise intensity detection,which outperforms traditional algorithms, with the system achieving a classification performance of 0.933 sensitivity, 0.802 specificity, and 0.960 accuracy. To further improve the system, we combine HRV with the linear features of PCG. Our exercise intensitydetection system achieves 90.2% specificity, 96.7% recall, and 98.1% accuracy in five-fold cross-validation.

关 键 词：heart rate variability(HRV) phonocardiogram(PCG) Unet temporal convolutionalnetwork(TCN) machine learning exercise intensity 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] G804.7[自动化与计算机技术—控制科学与工程]