Development and educational practice of response evaluation system for children with severe motor and intellectual disabilities using artificial intelligence.

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K20258
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: :Education and related fields
• Research Institution: Ibaraki University
• Principal Investigator: Ishida Osamu 茨城大学, 教育学部, 講師 (50909926)
• Project Period (FY): 2021-08-30 – 2024-03-31
• Keywords: 重症心身障害 / 心拍 / 人工知能 / 応答評価システム

Outline of Final Research Achievements

This study aims to establish a method for grasping the actual conditions of children with severe motor and intellectual disabilities (SMID) that teachers can easily implement. These teachers do not have specialized knowledge and skills in measuring equipment and heart rate variability. Collaborating with a company, we developed a response evaluation system for SMID using artificial intelligence. In developing the response evaluation system, we found that critically-ill children often exhibit involuntary movements and that noise tends to be introduced during measurement. Therefore, we developed a judgment algorithm for an AI tool that evaluates heart rate variability related to psychological states and unrelated heart rate variability after correcting the biometric data with a quadratic or cubic spline function to reduce noise based on body movements. A patent application was filed to obtain the rights to the research results.

Free Research Field

特別支援教育

Academic Significance and Societal Importance of the Research Achievements

重症児は，教員の働きかけに対する応答が乏しいことから，行動観察による感覚機能や興味・関心などの実態把握が困難で，それが教育実践における課題となっていた。本研究は，重症児の応答の評価に人工知能を活用する初めての研究であり，重症児の実態把握に新たな方法論を提示する点に学術的意義がある。また，本研究で活用した心拍などの生理指標の分析・解釈には専門的な知識と習熟が必要で，教員が実施するのは難しいという課題もあった。本研究で開発した応答評価システムを活用することで，重症児の感覚機能や興味・関心を簡便に評価できるようになるとともに，実証データに基づく重症児教育の質の向上に寄与しうる点に社会的意義がある。