Department of Surgery & Cancer, Imperial College London, St. Mary's Hospital, London W2 1NY, UK.
Institute of Global Health Innovation, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
Sensors (Basel). 2022 Sep 13;22(18):6920. doi: 10.3390/s22186920.
Wearable technologies are small electronic and mobile devices with wireless communication capabilities that can be worn on the body as a part of devices, accessories or clothes. Sensors incorporated within wearable devices enable the collection of a broad spectrum of data that can be processed and analysed by artificial intelligence (AI) systems. In this narrative review, we performed a literature search of the MEDLINE, Embase and Scopus databases. We included any original studies that used sensors to collect data for a sporting event and subsequently used an AI-based system to process the data with diagnostic, treatment or monitoring intents. The included studies show the use of AI in various sports including basketball, baseball and motor racing to improve athletic performance. We classified the studies according to the stage of an event, including pre-event training to guide performance and predict the possibility of injuries; during events to optimise performance and inform strategies; and in diagnosing injuries after an event. Based on the included studies, AI techniques to process data from sensors can detect patterns in physiological variables as well as positional and kinematic data to inform how athletes can improve their performance. Although AI has promising applications in sports medicine, there are several challenges that can hinder their adoption. We have also identified avenues for future work that can provide solutions to overcome these challenges.
可穿戴技术是具有无线通信功能的小型电子和移动设备,可以作为设备、配件或衣服的一部分佩戴在身上。可穿戴设备中包含的传感器能够收集广泛的各种数据,这些数据可以通过人工智能 (AI) 系统进行处理和分析。在这篇叙述性综述中,我们对 MEDLINE、Embase 和 Scopus 数据库进行了文献检索。我们纳入了任何使用传感器收集运动事件数据并随后使用基于 AI 的系统处理具有诊断、治疗或监测意图的数据的原始研究。纳入的研究表明,人工智能可用于各种运动,包括篮球、棒球和赛车运动,以提高运动员的表现。我们根据事件的阶段对研究进行了分类,包括赛前训练以指导表现和预测受伤的可能性;在比赛中优化表现并提供策略信息;以及在赛后诊断受伤。根据纳入的研究,用于处理传感器数据的 AI 技术可以检测生理变量以及位置和运动学数据中的模式,以告知运动员如何提高表现。尽管人工智能在运动医学中有很有前途的应用,但也存在一些挑战可能会阻碍其采用。我们还确定了未来工作的方向,可以提供解决方案来克服这些挑战。