1997年北陸先端科学技術大学院大学情報科学研究科博士後期課程修了.同年 (株)ATR知能映像通信研究所客員研究員.2001年公立はこだて未来大学情報アーキテクチャ学科助教授,2005年同学科教授.2009年北海道大学大学院情報科学研究科教授,2019年同大学院情報科学研究院教授,2023年同特任教授.博士(情報科学).ヒューマンエージェントインタラクション(HAI),ヒューマンロボットインタラクション(HRI),ロボット情報学,インタラクティブシステム,環境知能,情報科学,人工知能に関する研究に従事.情報処理学会フェロー.人工知能学会,ロボット学会,電子情報通信学会,ヒューマンインタフェース学会,ACM,各会員.
In recent years, gesture recognition using surface-electromyogram (sEMG) has become popular and these approaches can classify gestures at a high recognition rate. In particular, easily-mountable sEMG based gesture recognition devices have been developed. When developing such devices for use in daily lives, it is necessary to consider situations where users will be using the device while gripping objects, such as umbrellas, bags and so on. By using sEMG of the forearm, it is possible to still collect data without intruding on what the user is doing in these situations. However, sEMG based gesture recognition while gripping an object still lacks sufficient investigation. Therefore, in this study, in order to investigate the feasibility of gesture input while gripping an object, we performed an experiment to measure recognition accuracy for four hand gestures of users while they are holding a variety of objects. From the results, we discuss both feasibility and problems of gesture input while gripping objects and propose a new approach to resolve those problems.