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Applying statistical parametric mapping regression to identify key kinematic characteristics of underwater dolphin
Shuxin Wang1,2, Yuanhao Li3, Xiaotong Chen1
1School of Physical Education and Sports Science, South China Normal University, Guangzhou, China.
Abstract:
The purpose of this study was to systematically explore the key kinematic factors influencing swimming velocity during the underwater dolphin kick (UDK) using statistical parametric mapping regression. Twenty-one university swimmers (16 males and 5 females) had a personal best within 20% of the world record. This study adopted a quantitative cross-sectional experimental design to identify phase-specific relationships between kinematic variables and swimming velocity during UDK. Their performances were recorded and analysed using two-dimensional (2D) video analysis. Twenty-one regression models revealed six key kinematic variables significantly associated with UDK velocity: the mean vertical velocity of the fifth metatarsal phalangeal joint, maximum vertical velocity of the fifth metatarsal phalangeal joint, maximum knee angle, minimum knee angle, minimum ankle angle, and mean angular velocity of the knee. Increases in these variables corresponded to higher swimming velocity. These findings provide a detailed understanding of the phase-specific contributions of lower-limb kinematics to UDK performance and offer practical implications for optimising training strategies.
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