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Elite Tennis Players Experiencing High-Arched Supination and Cuboids Dropped Foot Syndromes in Daily Normal Gait.

Tong-Hsien ChowChin-Chia Hsu
Published in: International journal of environmental research and public health (2022)
Many studies have focused on the plantar pressure characteristics of specific movements and footwork in tennis. However, little research has been conducted for exploring the foot characteristics among tennis professionals' daily habitual paces. This study aims to examine the pressure profiles associated with foot posture and balance abilities of elite tennis players during normal gait to understand how foot loading patterns result from habitual paces that may be derived from intensive tennis training and competition. A cross-sectional comparative study is conducted on 95 male college elite tennis players (mean age: 20.2 ± 1.2 years) and 100 male recreational tennis players (mean age: 19.8 ± 0.9 years). Bipedal plantar pressure distributions (PPDs) associated with arch index (AI) and centers of gravity balance are explored through the plantar pressure device. The foot posture is estimated to determine the rearfoot postural alignment. During the midstance phase of walking with a normal gait, the bipedal AI values of the elite group are significantly lower, indicating that they have high-arched feet. Additionally, the elite group experienced higher PPDs at the lateral regions of their longitudinal arches and heels and relatively lower PPDs at the medial portions of both feet. Rearfoot postural alignment resonance analysis of the PPDs suggests that the elite group experienced foot supination associated with cuboid dropped. Moreover, the right foot bears heavier centers of gravity balance in the present study. The elite tennis players in the study are categorized as having high-arched supination with cuboids dropped when performing daily habitual paces. This finding warrants further investigation into the correlation between possible injuries and daily habitual paces that may result from tennis' intensive training and competition.
Keyphrases
  • body composition
  • physical activity
  • artificial intelligence
  • machine learning
  • minimally invasive