2023 Fiscal Year Final Research Report

Development and Evaluation of Self-Body Recognition Task for Young Children Using Gamification and Machine Learning

Research Project

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Project/Area Number	19H04019
Research Category	Grant-in-Aid for Scientific Research (B)
Allocation Type	Single-year Grants
Section	一般
Review Section	Basic Section 59030:Physical education, and physical and health education-related
Research Institution	Otsuma Women's University
Principal Investigator	Miyazaki Michiko 大妻女子大学, 社会情報学部, 准教授 (90526732)
Co-Investigator(Kenkyū-buntansha)	浅井智久株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 主任研究員 (50712014) 麦谷綾子日本女子大学, 人間社会学部, 准教授 (70447027)
Project Period (FY)	2019-04-01 – 2023-03-31
Keywords	身体地図 / 自己像 / 発達 / 自己 / ゲーミフィケーション
Outline of Final Research Achievements	Despite its popularity as an index of self-recognition, the mark test has not been used for assessing representations of the bodily self. This study combines the mark test and cross-reality task, to demonstrate novel aspects of children’s body representation and its development. Participants' real-time skeletal data was captured, and virtual marks were displayed on 30 body parts for participants to interact through touch. The accuracy and trajectory of the first touch and reaction time were analyzed. Thirty Japanese 2- and 3-year-olds participated. Localization error could be predicted by dynamical body part coordination. Three-year-olds displayed fast and predictive reaching instead of visually guided reaching. Analyzing hand-reaching strategies in the XR mark test revealed aspects of the development of sensorimotor body representations.
Free Research Field	認知科学
Academic Significance and Societal Importance of the Research Achievements	我々が開発したXRマークテストは古典的マークテストの新たな可能性を提供し、自己身体表象の発達を評価する有効な方法となる。また、身体的自己認識の発達に関する知見に加え、本研究で用いたAI統計学的アプローチは、認知科学の発達分野への大きな貢献をもたらす。身体部位の協調とリーチングの軌跡の分析を通して、子どもの内部モデルの出現と予測的リーチングを検出する方法を提供した。この方法論は、他の発達領域にも応用できる可能性があり、感覚運動と認知過程の発達に関する新たな洞察を明らかにするために役立つ。認知科学発達分野におけるAIと統計学の統合は、人間の発達の理解を進める上で大きな可能性を秘めている。