在足球运动员中使用智能手机传感器系统和临床医生领导的修改BESS测试进行平衡评估,这些运动员患有部相关疼痛:一项探索性横截面研究
Alexander Puyol1, Matthew King2, Charlotte Ganderton1
1School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083, Australia.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
智能手机的传感器准确地检测出部疼痛的足球运动员的平衡缺陷,优于传统方法. 这项技术增强了临床评估,以更好地平衡决策.
科学领域:
- 运动医学 运动医学
- 生物力学 生物力学
- 数字健康数字健康
背景情况:
- 平衡错误评分系统 (BESS) 是一种标准但有限的工具,用于评估静态姿势平衡.
- 它对视觉观察的依赖导致了低级别之间的可靠性和错过的诊断,特别是在运动员中.
- 智能手机的运动传感器为定量,客观的平衡评估提供了一个潜在的解决方案.
研究的目的:
- 为了评估基于智能手机的新型系统的区分有效性,用于远程平衡测量.
- 将智能手机平衡量度与足球运动员修改后的BESS测试进行比较.
- 为了识别带有和没有部疼痛的运动员之间的平衡差异.
主要方法:
- 一项涉及64名澳大利亚足球运动员 (18-40岁) 的探索性横截面研究.
- 平衡测试 (单体和双体姿势) 使用修改后的BESS获得分数,并通过智能手机设备量化.
- 统计分析包括探索因素分析 (EFA),集群接收器操作特征 (ROC) 与曲线下的面积 (AUC) 以及线性混合效应ANCOVA.
主要成果:
- 对于智能手机测量和修改的BESS分数,EFA表示了不同的因子.
- 在单腿姿势中,智能手机摇摆测量 (前后,中侧) 在区分关节疼痛组中显示可接受到极佳的准确性 (AUC = 0.72-0.80).
- 与没有部疼痛的运动员相比,部疼痛的运动员表现出明显较少的单腿平衡变化和幅度 (p <0.05).
结论:
- 智能手机技术在静态平衡任务中有效地区分患有和没有部疼痛的人.
- 将智能手机平衡评估与修改后的BESS集成,可以优化临床评估.
- 需要进一步的研究来探索智能手机用于动态平衡评估的使用.
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