Arzehgar Afrooz, Seyedhasani Seyedeh Nahid, Ahmadi Fatemeh Baharvand, Bagheri Baravati Fatemeh, Sadeghi Hesar Alireza, Kachooei Amir Reza, Aalaei Shokoufeh
Department of medical informatics, Faculty of medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Rothman Orthopaedics Florida at AdventHealth, Orlando, FL, USA.
BMC Sports Sci Med Rehabil. 2025 Jan 30;17(1):15. doi: 10.1186/s13102-025-01063-z.
Insightful motion analysis provides valuable information for athlete health, a crucial aspect of sports medicine. This systematic review presents an analytical overview of the use of various sensors in motion analysis for sports injury assessment.
A comprehensive search of PubMed/MEDLINE, Scopus, and Web of Science was conducted in February 2024 using search terms related to "sport", "athlete", "sensor-based technology", "motion analysis", and "injury." Studies were included based on PCC (Participants, Concept, Context) criteria. Key data, including sensor types, motion data processing methods, injury and sport types, and application areas, were extracted and analyzed.
Forty-two studies met the inclusion criteria. Inertial measurement unit (IMU) sensors were the most commonly used for motion data collection. Sensor fusion techniques have gained traction, particularly for rehabilitation assessment. Knee injuries and joint sprains were the most frequently studied injuries, with statistical methods being the predominant approach to data analysis.
This review comprehensively explains sensor-based techniques in sports injury motion analysis. Significant research gaps, including the integration of advanced processing techniques, real-world applicability, and the inclusion of underrepresented domains such as adaptive sports, highlight opportunities for innovation. Bridging these gaps can drive the development of more effective, accessible, and personalized solutions in sports health.
深入的运动分析为运动员健康提供了有价值的信息,这是运动医学的一个关键方面。本系统综述对各种传感器在运动分析中用于运动损伤评估的应用进行了分析概述。
2024年2月,使用与“运动”、“运动员”、“基于传感器的技术”、“运动分析”和“损伤”相关的检索词,对PubMed/MEDLINE、Scopus和Web of Science进行了全面检索。根据PCC(参与者、概念、背景)标准纳入研究。提取并分析了关键数据,包括传感器类型、运动数据处理方法、损伤和运动类型以及应用领域。
42项研究符合纳入标准。惯性测量单元(IMU)传感器是最常用于运动数据收集的传感器。传感器融合技术越来越受到关注,特别是在康复评估方面。膝关节损伤和关节扭伤是研究最频繁的损伤,统计方法是数据分析的主要方法。
本综述全面解释了基于传感器的技术在运动损伤运动分析中的应用。重大的研究空白,包括先进处理技术的整合、实际适用性以及纳入如适应性运动等代表性不足的领域,凸显了创新机会。弥合这些差距可以推动运动健康领域更有效、可及和个性化解决方案的发展。