A Feasibility Study of the Effect of Feature Differences in Onomatopoeia on Physical Movement Using Machine Learning

Abstract

In this study, we investigated the effects of onomatopoeia instructions on physical actions in sports coaching. We used a thin-film pressure sensor (Force Sensing Resistor) embedded in a handball. We measured grip pressure data from undergraduate and graduate students under various onomatopoeic instructions. We also investigated subjective interpretations of each onomatopoeia. We applied machine learning-based clustering method to examine differences in grip motion patterns by onomatopoeia type. We explored the relationship between phonological characteristics of onomatopoeia and actual physical movement data. Our results indicate that onomatopoeic instructions influence movement through multiple factors, involving both individual interpretation and physical expression, rather than simple one-to-one correspondence.