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Tundra lists 2 Lower Extremity Performance clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT07711379
Immediate Effects of Ankle Joint Mobilization on Jump Performance in Healthy University Students
The purpose of this randomized controlled study is to investigate the immediate effects of ankle joint mobilization on countermovement jump performance and ankle dorsiflexion range of motion in healthy university students. Participants will be randomly assigned to either an ankle joint mobilization group or a sham mobilization group. Countermovement jump performance will be assessed using the My Jump Lab mobile application, and ankle dorsiflexion range of motion will be measured using the weight-bearing lunge test with a digital inclinometer before and immediately after the intervention. The findings of this study are expected to improve the understanding of the acute effects of ankle joint mobilization on functional performance and ankle mobility.
Gender: All
Ages: 18 Years - 30 Years
Updated: 2026-07-17
1 state
NCT07677371
Position-Specific Lower Limb Performance and AI-Based Injury Risk Analysis in Young Male Basketball Players
This observational study aims to evaluate lower extremity performance characteristics in young male basketball players according to their playing positions and to explore injury risk patterns using artificial intelligence (AI)-based analysis. Basketball requires frequent jumping, sprinting, rapid changes of direction, acceleration, deceleration, and single-leg movements, all of which place significant demands on lower extremity function. Participants will undergo a single assessment session including anthropometric measurements and performance tests such as countermovement jump, reactive strength testing, single-leg performance tests, and agility assessments. Information regarding previous lower extremity injuries, training history, and playing position will also be collected. The study will compare performance characteristics among different basketball positions, including guards, forwards, and centers. In addition, AI and machine learning techniques will be used to analyze the collected performance data and identify patterns associated with injury risk. The purpose of the AI analysis is not to diagnose injuries but to investigate whether combinations of performance variables can help identify athletes who may demonstrate higher-risk movement or performance profiles. The findings may contribute to the development of position-specific training strategies, individualized performance monitoring, and evidence-based injury prevention approaches in youth basketball players.
Gender: MALE
Ages: 12 Years - 18 Years
Updated: 2026-06-30