Sensor-based technologies for motion analysis in sports injuries: a scoping review
(Sensorbasierte Technologien für die Bewegungsanalyse bei Sportverletzungen: eine Übersichtsstudie)
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.
© Copyright 2025 BMC Sports Science, Medicine and Rehabilitation. BioMed Central. Alle Rechte vorbehalten.
| Schlagworte: | |
|---|---|
| Notationen: | Naturwissenschaften und Technik Biowissenschaften und Sportmedizin |
| Tagging: | Bewegungsanalyse |
| Veröffentlicht in: | BMC Sports Science, Medicine and Rehabilitation |
| Sprache: | Englisch |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://doi.org/10.1186/s13102-025-01063-z |
| Jahrgang: | 17 |
| Seiten: | 15 |
| Dokumentenarten: | Artikel |
| Level: | hoch |