Exploring Possibility of Skill Scoring using Motion Sensory BigData

【 Research Outline 】

The popular applications in the sports market have been using human movement data acquired by small sensors. The conventional biomechanics and sports science field define human movement by mathematical average model derived from featured points of the movement. Parameters selected from the model are applied to the final model provision. However, if the model can be found without applying such parameters, breakthrough can be provided to the new movement analysis method that accelerates health management and skill analysis. This research project applies a machine learning approach to human movement bigdata such as movies and sensor data recorded from human movement and tries to find a new method that automatically build a skill model. Read More

Conference Proceedings

  1. Shinichi Yamagiwa, Yoshinobu Kawahara, Noriyuki Tabuchi, Yoshinobu Watanabe, Takeshi Naruo. Skill grouping method: Mining and clustering skill differences from body movement BigData, 2015 IEEE International Conference on Big Data (Big Data), , (2015-10-29), DOI:10.1109/bigdata.2015.7364049