Identification of Subtle Differences in Football-Stopping Movements Based on Machine Learning
The application of wearable devices based on microsensors in various sports is booming.Although smart wristbands have been applied in various fields,their diversity in sports still needs further exploration.At present,most research focuses on the recognition of different actions,but there is relatively little analysis of subtle differences in the same action.In this work,researchers captured the subtle movements of a football when it stopped by wearing an intelligent wrist strap with a 6-degree of freedom inertial measurement unit,and analyzed the subtle movements of the football movement.By using machine learning algorithms to learn the extracted action features,two states of each subtle action are identified.The results indicate that capturing and analyzing subtle movements in motion can help provide practical motion guidance.
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