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. 2025 Jan 30;17(1):15.
doi: 10.1186/s13102-025-01063-z.

Sensor-based technologies for motion analysis in sports injuries: a scoping review

Affiliations

Sensor-based technologies for motion analysis in sports injuries: a scoping review

Afrooz Arzehgar et al. BMC Sports Sci Med Rehabil. .

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Feedback; Injury; Motion analysis; Rehabilitation; Sensor; Sport.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the Ethics Committee of Mashhad University of Medical Sciences and Medical School (Ethical code: IR.MUMS.MEDICAL.REC.1403.145). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
PRISMA flow diagram for article selection
Fig. 2
Fig. 2
Characteristics of the included studies. The following variables are shown: a) publication year, b) sports categories, c) sensor type, d) injury type, e) motion analysis methods, and f) aim of the application
Fig. 3
Fig. 3
Placement of sensors on the body for motion analysis in different studies

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