Study on a multi-purpose care scheduling system linked to detecting abnormalities in the care recipient.

2022 Fiscal Year Final Research Report

• Project/Area Number: 17K01573
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Rehabilitation science/Welfare engineering
• Research Institution: Okayama Prefectural University
• Principal Investigator: Kanagawa Akihiro 岡山県立大学, 情報工学部, 教授 (70204534)
• Co-Investigator(Kenkyū-buntansha): 滝本 裕則 岡山県立大学, 情報工学部, 准教授 (10413874)
• Project Period (FY): 2017-04-01 – 2023-03-31
• Keywords: 介護・看護スケジューリング / 見守りシステム

Outline of Final Research Achievements

This study addressed an abnormality detection for older people and the caregiver scheduling method. For abnormality detection, we focused on falls as an abnormal behavior condition. As a result of the research, the effectiveness of applying a continuous wavelet transform to the information obtained from the acceleration sensor was confirmed. In addition, we proposed a method for estimating the state of a subject using a RGB-D sensor as a privacy-conscious method for estimating the patient's condition. On the other hand, regarding the nursing care schedule, measures against the spread of the new coronavirus have been a pressing social issue since the start of the study. Considering this social need, we studied a solution method for the nurse work schedule problem that considers the current situation where the infection affects the staff in the medical field.

Free Research Field

情報数理学，画像工学

Academic Significance and Societal Importance of the Research Achievements

本課題では、介護サービスに関するハードウェアならびにソフトウェアについて、情報工学的手法を用いて限られた資源を有効に活用することで、被介護者が安心して過ごせる環境を実現するとともに、介護スタッフを多方面から支援し職員満足の向上を実現するシステムを構築した。我々が提案する技術は、介護業務の部分的ではあるが負荷軽減にも繋がるものであり、超高齢化社会を迎える我が国において重要な基盤技術になると考える。