Prediction of Lower Extremity Injuries Using Lower Limb-worn Inertial Measurement Units

NCT07289828 | Completed

• 1 other identifier: KneeInjuryPred
• Study Type: observational
• Target: 108
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

prediction; ankle injury; knee injury; inertial sensor; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• IMU data

  Time-stamped, unfiltered, device-coordinate-based 3-axis IMU data (Ax, Ay, Az) from four IMUs, placed laterally on both thighs (above the knee joint) and on both ankles (above the lateral malleolus).

  at baseline

Secondary Outcomes (3)

• questionnaire injuries lower extremity

  Baseline

• questionnaire sports activity

  Baseline

• questionnaire prevention

  baseline

Study Arms (1)

test group

All participants were sports students at TUM School of Medicine and Health. Of all participants, inertial sensor data were collected during walking and running on a defined track (5 minutes walking, 5 minutes running, 5 minutes walking on a standard 400 m oval tartan track). All participants completed questionnaires regarding previous injuries, comorbidities, sports activity, and preventive measures undertaken.

Other: IMU Data collection; Other: Questionnaire

Interventions

IMU Data collection OTHER

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).

test group

Questionnaire OTHER

On the day of the examination, the test subjects completed a standardized questionnaire on previous injuries, type of sport, sporting activity, and preventive measures.

test group

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Sport students at TUM School of Medicine and Health

You may qualify if:

• Subjectively healthy participants
• Age: \>18 years and under 60 years
• German language skills sufficient to follow the exercise instructions and complete the questionnaires

You may not qualify if:

• Age \<18 years or \>60 years
• Recent injuries and trauma to the lower extremities (less than 6 months ago)
• Acute malignant disease
• Acute inflammatory disease
• Lack of German language skills
• Lack of cardiopulmonary endurance for testing

Sponsors & Collaborators

• Technical University of Munich: lead

Study Sites (1)

TUM University Hospital

Munich, Bavaria, 81675, Germany

Location

MeSH Terms

Conditions

Ankle Injuries; Knee Injuries

Interventions

Surveys and Questionnaires

Condition Hierarchy (Ancestors)

Leg Injuries; Wounds and Injuries

Intervention Hierarchy (Ancestors)

Data Collection; Epidemiologic Methods; Investigative Techniques; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Study Officials

• Rüdiger von Eisenhart-Rothe, Prof. Dr. med.

  Department of Orthopaedics and Sports Orthopaedics, TUM University Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Senior physician

Study Record Dates

• First Submitted: December 4, 2025
• First Posted: December 17, 2025
• Study Start: January 29, 2024
• Primary Completion: June 4, 2024
• Study Completion: June 4, 2024
• Last Updated: December 17, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

DE (1)