Use of Sample Entropy to Assess Sub-Maximal Physical Load for Avoiding Exercise-Induced Cardiac Fatigue

• DOI: 10.3390/app13063813
• Publication Date: 2023-03-17T06:59:26Z
• Authors: Yu-Han Lai; Po-Hsun Huang; Tzu-Chien Hsiao
• Keywords: Sample entropy

Sub-maximal physical load (sub-max) training is optimal for athletes. However, few methods can directly assess whether sub-max. Therefore, this study aimed to identify metrics that could sub-max by predicting maximal load, helping athletes avoid the risks associated with training. Physiological data were collected from 30 participants in a bicycle incremental exercise experiment, including R-R interval (RR), stroke volume (SV), breath-to-breath (BB), and breathing rate (BR). Sample Entropy (SampEn) analysis was used complexity of physiological data. BR increased time but not be stage; however, SampEn BB effectively stage (p < 0.05), as novel indicators SV cardiac output 0.01). This also identified threshold value each sub-max, which sports science indicator The results suggest SampEn-based load. These findings guide quantitative healthcare.