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<p>The study explored the relationships between hand movement patterns and overall kinematic indicators of front-crawl sprint technique in boys aged 12–14, while considering the role of the morpho-functional profile. The sample consisted of 41 participants. Data were collected from anthropometric measurements (8 variables), a 20-s arm-cranking test (6 variables), and a 25-m front crawl trial. Swimming motion was characterized using inertial measurement unit sensors (IMU; BlueTrident) and Artificial Intelligence (8 variables). Video analysis was used to determine swimming velocity (v), stroke rate (SR), stroke length (SL), and stroke index (SI). Principal Component Analysis identified five components: Large Body Size (LBS), Low Fat (LF), Enormous Power (EP), Dynamism (D), and High Angular Velocity (HAV). Pearson correlation analysis revealed strong associations between LBS and EP (<i>r</i> = 0.85), as well as between D and EP (<i>r</i> = 0.51) and D and LBS (<i>r</i> = 0.34). Velocity was related to LBS, EP, D, and LF (<i>r</i> = 0.38–0.56). SR showed strong associations with D (<i>r</i> = 0.76) and EP (<i>r</i> = 0.35), whereas SL was negatively associated with D (<i>r</i> = − 0.44). SI was related to LBS, LF, and EP (<i>r</i> = 0.38–0.49). Overall kinematic indicators are associated with hand acceleration and angular velocity, and IMU based technique assessment supports evaluation of how effectively young swimmers utilize their anthropometric–energetic potential.</p>

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Exploring associations between energetic and anthropometric characteristics with front crawl technique in young male swimmers using IMU sensors: a preliminary study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月8日

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  • Łukasz Wądrzyk,
  • Robert Staszkiewicz,
  • Kamil Sokołowski,
  • Marek Strzała,
  • Julia Badzińska,
  • Magdalena Żegleń,
  • Łukasz Kryst

摘要

The study explored the relationships between hand movement patterns and overall kinematic indicators of front-crawl sprint technique in boys aged 12–14, while considering the role of the morpho-functional profile. The sample consisted of 41 participants. Data were collected from anthropometric measurements (8 variables), a 20-s arm-cranking test (6 variables), and a 25-m front crawl trial. Swimming motion was characterized using inertial measurement unit sensors (IMU; BlueTrident) and Artificial Intelligence (8 variables). Video analysis was used to determine swimming velocity (v), stroke rate (SR), stroke length (SL), and stroke index (SI). Principal Component Analysis identified five components: Large Body Size (LBS), Low Fat (LF), Enormous Power (EP), Dynamism (D), and High Angular Velocity (HAV). Pearson correlation analysis revealed strong associations between LBS and EP (r = 0.85), as well as between D and EP (r = 0.51) and D and LBS (r = 0.34). Velocity was related to LBS, EP, D, and LF (r = 0.38–0.56). SR showed strong associations with D (r = 0.76) and EP (r = 0.35), whereas SL was negatively associated with D (r = − 0.44). SI was related to LBS, LF, and EP (r = 0.38–0.49). Overall kinematic indicators are associated with hand acceleration and angular velocity, and IMU based technique assessment supports evaluation of how effectively young swimmers utilize their anthropometric–energetic potential.