Exploring Possibility of Skill Scoring using Motion Sensory BigData

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K12639
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Sports science
• Research Institution: University of Tsukuba
• Principal Investigator: Yamagiwa Shinichi 筑波大学, システム情報系, 准教授 (10574725)
• Co-Investigator(Kenkyū-buntansha): 河原 吉伸 大阪大学, 産業科学研究所, 准教授 (00514796) ; 和田 耕一 筑波大学, システム情報系, 教授 (30175145) ; 山本 裕二 名古屋大学, 総合保健体育科学センター, 教授 (30191456) ; 門田 浩二 大阪大学, 医学系研究科, 助教 (50557220)
• Co-Investigator(Renkei-kenkyūsha): HIRATA Chiaki 十文字学園女子大学, 人間生活学部, 准教授 (80438895)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 動きビッグデータ / スキルグルーピング / 人工知能

Outline of Final Research Achievements

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.

Free Research Field

スポーツ科学