Prediction of Lower Extremity Injuries Using Lower Limb-worn Inertial Measurement Units
NCT07289828 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 108
Last updated 2025-12-17
Summary
This study analyses questionnaires and inertial sensor data from 108 sports science students regarding previous lower extremity injuries, sports activity, and preventive measures, combined with the prospective development of an AI-based prediction algorithm.
Inertial sensor data were collected during walking and running on a standard 400 m track, with sensors placed on the thighs and ankles, and heart rate recorded via smartwatch. Participants also completed questionnaires on previous injuries, comorbidities, sports activity, and prevention.
The aim is to use the anonymized data to identify gait and running patterns associated with prior knee and ankle injuries using AI analysis, and to correlate these findings with sports activity and preventive measures.
Hypothesis: Prior lower extremity injuries leave specific gait and running patterns detectable by inertial sensors and AI-based analysis.
Conditions
- Lower Extremity Injuries
Interventions
- OTHER
-
IMU Data collection
Participants were walking and running while wearing inertial measurement units (IMU) on both legs. The IMUs (MetaMotionS sensor by Mbientlab) where recording at 100Hz (accelerometer and gyroscope) and 25Hz (magnetometer).
- OTHER
-
Questionnaire
On the day of the examination, the test subjects completed a standardized questionnaire on previous injuries, type of sport, sporting activity, and preventive measures.
Sponsors & Collaborators
-
Technical University of Munich
lead OTHER
Principal Investigators
-
Rüdiger von Eisenhart-Rothe, Prof. Dr. med. · Department of Orthopaedics and Sports Orthopaedics, TUM University Hospital
Eligibility
- Min Age
- 18 Years
- Max Age
- 60 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2024-01-29
- Primary Completion
- 2024-06-04
- Completion
- 2024-06-04
Countries
- Germany
Study Locations
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