Sports, Volume 13, Issue 2
2025 February - 34 articles
Cover Story: Heart rate variability (HRV) is a non-invasive health and fitness indicator, and machine learning (ML) has emerged as a powerful tool for analysing large HRV datasets. This study aims to identify athletic characteristics using HRV and ML algorithms. Two models were developed: Model 1 (M1) differentiated athletes from non-athletes; Model 2 (M2) aimed to identify a specific soccer player within a team. We proposed an athleticism index and a soccer identification index based on the performance of these algorithms. According to the results, these methods can effectively generate indices based on HRV to identify people with athletic characteristics or athletes with specific sports profiles. These findings suggest that HRV-based tests can provide valuable insights when integrated rigorously and systematically into daily training routines. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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