Position-Specific Lower Limb Performance and AI-Based Injury Risk Analysis in Young Male Basketball Players
2026년 6월 24일 업데이트: Istanbul Gelisim University
Position-Specific Lower Extremity Performance and Artificial Intelligence-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.
연구 개요
상태
완전한
연구 유형
관찰
등록 (실제)
81
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 장소
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Istanbul, 터키 (Türkiye), 34290
- Istanbul Gelisim University
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
공부할 수 있는 나이
- 어린이
- 성인
건강한 자원 봉사자를 받아들입니다
예
샘플링 방법
비확률 샘플
연구 인구
The study population consists of youth male basketball players competing at the developmental level.
Participants are recruited from basketball clubs and youth training programs and are classified according to their primary playing position, including point guard, shooting guard/small forward, power forward, and center.
설명
Inclusion Criteria:
- Male basketball players aged 12 to 18 years.
- Registered youth basketball athletes.
- Participation in regular basketball training for at least 1 year.
- Participation in basketball training at least 3 times per week.
- No acute lower extremity injury affecting performance testing within the previous 6 months.
- Ability to understand and follow testing instructions.
- Written informed consent provided by a parent or legal guardian and assent provided by the participant.
Exclusion Criteria:
- Lower extremity surgery within the previous 6 months.
- Acute musculoskeletal injury affecting test performance.
- Neurological, vestibular, or severe orthopedic conditions affecting balance, coordination, or motor performance.
- Pain, illness, fatigue, or any health condition that could affect performance on the assessment day.
- Cardiovascular or systemic conditions preventing completion of the testing protocol.
- Incomplete performance testing data or technically invalid measurements.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
코호트 및 개입
그룹/코호트 |
개입 / 치료 |
|---|---|
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Point Guard Players
Young male basketball players whose primary playing position is point guard.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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Participants will complete lower extremity performance tests including countermovement jump, reactive strength index testing, single-leg performance tests, and agility/change-of-direction assessments.
Performance data will be analyzed using artificial intelligence-based methods to explore injury risk patterns.
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Shooting Guard / Small Forward Players
Young male basketball players whose primary playing position is shooting guard or small forward.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysi
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Participants will complete lower extremity performance tests including countermovement jump, reactive strength index testing, single-leg performance tests, and agility/change-of-direction assessments.
Performance data will be analyzed using artificial intelligence-based methods to explore injury risk patterns.
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Power Forward Players
Young male basketball players whose primary playing position is power forward.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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Participants will complete lower extremity performance tests including countermovement jump, reactive strength index testing, single-leg performance tests, and agility/change-of-direction assessments.
Performance data will be analyzed using artificial intelligence-based methods to explore injury risk patterns.
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Center Players
Young male basketball players whose primary playing position is center.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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Participants will complete lower extremity performance tests including countermovement jump, reactive strength index testing, single-leg performance tests, and agility/change-of-direction assessments.
Performance data will be analyzed using artificial intelligence-based methods to explore injury risk patterns.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Countermovement Jump Height
기간: Baseline assessment (single session)
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Vertical jump height measured during the countermovement jump (CMJ) test using an artificial intelligence-based performance assessment system.
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Baseline assessment (single session)
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Reactive Strength Index (RSI)
기간: Baseline assessment (single session)
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Reactive strength performance calculated from jump height and ground contact time during reactive jump testing.
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Baseline assessment (single session)
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AI-Based Injury Risk Classification Score
기간: Baseline assessment (single session)
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Injury risk profile generated using artificial intelligence and machine learning algorithms based on lower extremity performance variables, asymmetry measures, agility performance, and injury history.
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Baseline assessment (single session)
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Single-Leg Hop Performance
기간: Baseline assessment (single session)
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Distance and performance outcomes obtained from right and left single-leg hop tests used to evaluate unilateral lower extremity function and limb asymmetry.
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Baseline assessment (single session)
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Time to Complete the T-Test Agility Assessment (seconds)
기간: Baseline assessment (single session)
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Time required to complete the standardized T-Test agility assessment.
Lower completion times indicate superior agility and change-of-direction ability in young basketball players.
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Baseline assessment (single session)
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Limb Symmetry Index Calculated from Single-Leg Countermovement Jump Height (%)
기간: Baseline assessment (single session)
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Limb Symmetry Index (LSI) calculated as the ratio between dominant and non-dominant lower extremity performance during the single-leg countermovement jump test.
Values closer to 100% indicate greater inter-limb symmetry.
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Baseline assessment (single session)
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Previous Lower Extremity Injury History
기간: At study enrollment
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Self-reported history of lower extremity injuries occurring within the previous 12 months.
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At study enrollment
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Countermovement Jump Height Measured by the D-Wall Athlete Performance System (cm)
기간: Baseline
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Countermovement jump height obtained from the D-Wall Athlete Performance System and compared among point guards, shooting guards/small forwards, power forwards, and centers.
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Baseline
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Acceleration and Deceleration Scores Measured by the D-Wall Athlete Performance System (%)
기간: Baseline
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Acceleration and deceleration performance scores generated by the D-Wall Athlete Performance System during athletic performance testing.
These scores quantify the athlete's ability to rapidly increase and decrease movement velocity.
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Baseline
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
2026년 5월 15일
기본 완료 (실제)
2026년 5월 22일
연구 완료 (실제)
2026년 5월 22일
연구 등록 날짜
최초 제출
2026년 6월 18일
QC 기준을 충족하는 최초 제출
2026년 6월 24일
처음 게시됨 (실제)
2026년 6월 30일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
2026년 6월 30일
QC 기준을 충족하는 마지막 업데이트 제출
2026년 6월 24일
마지막으로 확인됨
2026년 6월 1일
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
- IGU-SINTECH-BASKET-AI-2026-01
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
아니요
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아니
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아니
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