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スプリントインターバルトレーニングと青年期自由形水泳パフォーマンスの間の多変量動的関連分析
Xiaotong Chen1,2, Yankang Jiang1, Yupeng Shen3
1Sports Engineering Center, School of Sports Science, South China Normal University, Guangzhou, China.
BMC sports science, medicine & rehabilitation
|January 20, 2026
まとめ
複雑ネットワークモデリングは、トレーニング変数が水泳パフォーマンスに動的にどのように影響するかを明らかにする。速度、血中乳酸、自覚的運動強度などの主要因は、高強度インターバルトレーニング中に中心的な役割を果たすようになる。
科学分野:
- スポーツ科学;生理学;生体力学
背景:
- 複雑ネットワークモデリングは、スポーツにおける動的なトレーニング適応を分析するためにはあまり活用されていない。;高強度トレーニング中の多変量関係を理解することは、パフォーマンス最適化のために不可欠である。
研究 の 目的:
- 単一の水泳トレーニングセッション中の運動学的、代謝的、および知覚的変数間の動的な関連を分析するために複雑ネットワークモデリングを適用すること。;6x50mスプリントインターバルトレーニング(SSIT)プロトコルが100メートル自由形パフォーマンスおよび根本的な生理学的応答に及ぼす影響を調査すること。
主な方法:
- 複雑ネットワーク分析を用いて、ストローク数、ストローク長、血中乳酸、自覚的運動強度(RPE)、およびスイミング速度の関係の動的な関係を調べた。;データは、6x50m SSITプロトコル中に16人の青年期スイマーから収集された。
主要な成果:
- ネットワークトポロジーは安定したままであり、パフォーマンス向上のための集団的貢献を示唆している(密度は42.65%から49.17%に増加し、モジュラリティは0.2から0.24に増加)。;スイミング速度、血中乳酸、およびRPEのノード中心性は著しく増加し、パフォーマンスメディエーターとしての役割を強調している。;ストローク数は減少し、ストローク長はトレーニングセッション全体で安定していた。
結論:
- 複雑ネットワークモデリングは、トレーニングプロセスを動的に評価し、スイマーの適応メカニズムを理解するための新しいアプローチを提供する。;本研究は、無酸素能力が高強度インターバルトレーニング中にどのように形成されるかについての洞察を提供し、特定の変数が動的な役割を果たしている。
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