Clinical applications of wearable sensor-based gait analysis in athletes: a systematic review for injury prevention and rehabilitation.

backgroundGait analysis is fundamental for optimizing athletic performance and mitigating injury risks in sports medicine. While traditional laboratory assessments offer insights, the emergence of wearable sensor technology provides novel opportunities for objective, real-time gait evaluation in ecologically valid settings. This systematic review aims to (1) evaluate the clinical efficacy of wearable sensor-based gait analysis for injury prevention in athletes (2), examine its role in rehabilitation monitoring and clinical decision-making, and (3) identify methodological limitations and future research priorities required for standardized clinical integration.

methodsAdhering to PRISMA 2020 guidelines, a systematic search was conducted across MEDLINE, Web of Science, Scopus, and Embase from inception to May 31st, 2025. Studies investigating wearable sensor-based gait analysis in athletic populations for clinical applications (injury prevention, diagnosis, rehabilitation, or performance-related decision-making) were included. Data on study design, participant characteristics, sports, clinical conditions, sensor types, and gait parameters were extracted.

resultsFrom 2678 initial records, 22 studies (14 comparative, 8 non-comparative observational) met the inclusion criteria, encompassing 1040 participants: 841 athletes (weighted mean age: 25.7 years) and 199 healthy controls (weighted mean age: 31.4 years). Running (7 studies) and anterior cruciate ligament (ACL) injuries (6 studies) were the most frequently investigated sport and clinical condition, respectively. Inertial Measurement Units (IMUs) were the predominant sensor technology (59.1%), primarily assessing parameters like tibial shock, vertical ground reaction force, and spatio-temporal variables. Wearable sensors demonstrated emerging evidence of utility in identifying biomechanical alterations indicative of injury risk, monitoring fatigue, and guiding rehabilitation protocols. Key challenges identified include heterogeneity in methodologies, data accuracy concerns, and the need for standardized reporting.

conclusionWearable sensor-based gait analysis shows emerging evidence of providing objective biomechanical insights that may support injury risk assessment and rehabilitation monitoring in athletic populations. Evidence from moderate-quality observational studies indicates that simple, well-placed sensors may yield clinically meaningful information on loading and spatiotemporal control, complementing standard examination and decision-making in sports medicine. In practice, tibial accelerometers may be particularly useful for monitoring impact loads relevant to bone stress injuries, while trunk-mounted inertial measurement units show promise for providing spatiotemporal parameters to guide rehabilitation and return-to-play decisions. These applications are feasible in team and clinical environments, require minimal setup, and provide repeatable metrics that can directly inform athlete management. Broader adoption, however, will depend on improving methodological consistency, reporting standards, and integration with other clinical data sources. Future work using adequately powered samples and standardized sensor protocols will be essential to strengthen the evidence base and support clinical implementation.