Prediction of sports injuries by psychological process monitoring
Sports Psychiatry(2023)
摘要
Abstract: Objectives: Sports injuries usually have severe consequences for the concerned athletes as well as for trainers and teams. The question is if accidents can be predicted in specific cases. Can early-warning signals be detected in psychological time series? Methods: An App-based method of process-monitoring was applied for data collection of psychological parameters. Daily self-assessments using a Sports Process Questionnaire were realized by a professional soccer player during the after-care period of a psychiatric treatment. Methods for the prediction of critical events were applied (Dynamic Complexity, Recurrence Plots, dynamic inter-item correlations). Injuries may demarcate pattern transitions in the mental functioning of athletes, which could be identified by the Pattern Transition Detection Algorithm (PTDA). Results: Early-warning signals of the accident could be identified in the time series. Dynamic Complexity revealed a critical instability, Recurrence Plots a transient period, and the dynamic inter-item correlations a period of increased system coherence just before the accident. The PTDA revealed a phase transition at the occurring injury. Conclusions: Even if the analysis is based on a single case, the results are promising. Psychological self-reports allow a short-term prediction of bio-mechanical injuries and by this, can help to prevent them. Nonlinear measures can be applied to time series data collected by digital process monitoring.
更多查看译文
关键词
Elite football,precursors of sports injuries,non-linear methods,Synergetic Navigation System (SNS),Sports Psychiatry
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要