男子篮球精英赛中的运动员监控系统:挑战、建议和未来展望》。

IF 1.2 Q3 SPORT SCIENCES Translational sports medicine Pub Date : 2024-10-18 eCollection Date: 2024-01-01 DOI:10.1155/2024/6326566
Jakob Burger, Alexander-Stephan Henze, Thomas Voit, Richard Latzel, Othmar Moser
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引用次数: 0

摘要

运动员监测系统(AMS)为整合、处理、分析和绘制各种监测数据提供了一个集中平台,可帮助教练管理精英男子篮球运动员的严格要求,这些运动员经常参加高压力比赛,恢复时间极短。本综述总结了目前在部署体能监测系统方面面临的挑战,强调了其在预防损伤和优化表现方面的作用,并讨论了可提高其效用的技术进步。主要挑战包括根据人力和财力选择合适的监测方法、数据收集的准确性、实时数据处理以及训练方案的个性化。由于每种监测方法都存在弱点和局限性,建议将客观(如外部负荷数据、心率测量和生物标志物)和主观(运动员报告的结果测量)监测数据整合到 AMS 中,以便全面了解运动员的健康状况和准备情况。此外,集成到 AMS 中的决策支持系统可以帮助教练快速了解运动员的当前状况,并就日常负荷和恢复管理做出明智的决策。在这种情况下,从未来的角度来看,AMS 有可能结合预测分析和人工智能,进一步加强精英男子篮球的决策过程。我们的研究结果表明,需要不断创新和严格验证 AMS 技术,以确保它们能满足专业体育环境不断变化的需求。
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Athlete Monitoring Systems in Elite Men's Basketball: Challenges, Recommendations, and Future Perspectives.

Athlete monitoring systems (AMSs) provide a centralized platform for integrating, processing, analyzing, and graphing various monitoring data to help coaches manage the rigorous demands of elite men's basketball players, who frequently participate in high-stress games with minimal recovery time. This review synthesizes current challenges in deploying AMSs, underscores their role in injury prevention and performance optimization, and discusses technological advances that could enhance their utility. Key challenges include selecting appropriate monitoring methods based on human and financial resources, accuracy of data collection, real-time data processing, and personalization of training regimens. Due to the weaknesses and limitations of each monitoring method, it is recommended that both objective (e.g., external load data, heart rate measures, and biomarkers) and subjective (athlete-reported outcome measures) monitoring data be integrated into an AMS to provide a holistic insight of the athlete's health and readiness. In addition, decision support systems integrated into an AMS can help coaches quickly gain an overview of their players' current condition and make informed decisions about daily load and recovery management. In this context, future perspectives suggest the potential for AMSs to incorporate predictive analytics and artificial intelligence to further enhance decision-making processes in elite men's basketball. Our findings underscore the need for continued innovation and rigorous validation of AMS technologies to ensure they meet the evolving demands of professional sports environments.

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