Prediction of anterior cruciate ligament injury in basketball players using machine learning
Not Applicable
Completed
- Conditions
- Prevention of anterior cruciate ligament (ACL) injury in male basketball playersMusculoskeletal Diseases
- Registration Number
- ISRCTN18009799
- Lead Sponsor
- Hospital Universiti Sains Malaysia
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Completed
- Sex
- Male
- Target Recruitment
- 114
Inclusion Criteria
1. Male
2. Age over 18 years
3. Exercising =8 hours per week,
4. Having played basketball for at least 3 years
5. Having a negative Lachman's knee examination
Exclusion Criteria
1. Exercise-related or neurological disorders
2. Recent hip or knee surgery or trauma
3. Incomplete data not being analyzed
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Measured at baseline and 12 months:<br>1. The athlete's profile (height, weight, age, level of play, playing position), basketball training record, and self-reported injury history for each participant were recorded<br>2. Balance testing and joint mobility testing were conducted using YBT and FMS, with a duration of half an hour<br>3. Biomechanical and synchronized electromyography (EMG) experiments were performed, lasting for two hours<br>4. Trunk testing was conducted using DLH, strength testing was performed with 1-RM weighted squat and deadlift, explosive strength was assessed using countermovement jump (CMJ), squat jump (SJ), and drop jump (DJ), and agility testing was carried out with the Lane Agility Test lasting for two hours
- Secondary Outcome Measures
Name Time Method There are no secondary outcome measures