计算机科学
可穿戴计算机
区间(图论)
模拟
人工智能
数学
组合数学
嵌入式系统
作者
Kebao Zhang,B. Guo,Don‐Lin Yang,Yi Jia,Kehu Zhang,Liu Wang
标识
DOI:10.1038/s41598-024-82274-1
摘要
Flexible micro-sensors have significant application potential in the field of sports performance evaluation. The aim of this study is to assess sports performance by grip pressure using a MMSS sensor (MXene as the sensitive material and melamine sponge as the substrate, a type of flexible piezoresistive pressure sensor). The grip pressures of expert and amateur players are evaluated in single skills events (golf, billiards, basketball, javelin and shot put) and in skills conversion (badminton and tennis). Indicators (time nodes, intervals, peaks, etc.) related to grip pressure on the handle are collected, analyzed, and identified by artificial intelligence. Finally, the K-Nearest Neighbor (KNN) of artificial intelligence algorithms is employed to identify differences for 400 strokes of tennis players in interval training session. Expert tennis athlete exhibits a higher level of precision, concentration and stability for exert and release of grip force (KNN accuracy of train 95.0%) than amateur (KNN: 84.6%) during single movement, technical conversion, and interval training condition. This research offers a new perspective for evaluating sports performance in hand-held equipment events and presents a feasible direction for facing challenges of flexible wearable technology in practice.
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