Position-Specific Lower Limb Performance and AI-Based Injury Risk Analysis in Young Male Basketball Players
2026年6月24日 更新者：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.
調査の概要
状態
完了
条件
研究の種類
観察的
入学 (実際)
81
連絡先と場所
このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。
研究場所
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Istanbul、トルコ（Türkiye）、34290
- Istanbul Gelisim University
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参加基準
研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。
適格基準
就学可能な年齢
- 子
- 大人
健康ボランティアの受け入れ
はい
サンプリング方法
非確率サンプル
調査対象母集団
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.
説明
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.
研究計画
このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
|
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.
|
|
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
|
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.
|
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Countermovement Jump Height
時間枠：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)
時間枠：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
時間枠：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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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Single-Leg Hop Performance
時間枠：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)
時間枠：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 (%)
時間枠：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
時間枠：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)
時間枠：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 (%)
時間枠：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.
|
Baseline
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協力者と研究者
ここでは、この調査に関係する人々や組織を見つけることができます。
研究記録日
これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。
主要日程の研究
研究開始 (実際)
2026年5月15日
一次修了 (実際)
2026年5月22日
研究の完了 (実際)
2026年5月22日
試験登録日
最初に提出
2026年6月18日
QC基準を満たした最初の提出物
2026年6月24日
最初の投稿 (実際)
2026年6月30日
学習記録の更新
投稿された最後の更新 (実際)
2026年6月30日
QC基準を満たした最後の更新が送信されました
2026年6月24日
最終確認日
2026年6月1日
詳しくは
本研究に関する用語
その他の研究ID番号
- IGU-SINTECH-BASKET-AI-2026-01
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
いいえ
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
いいえ
米国FDA規制機器製品の研究
いいえ
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