Behavior-based Understanding of Elderly People with Dementia: A Hierarchical Classification of Daily Object Use

Abstract

Providing individualized daily living care is quintessentially important to ensure the quality of life for elderly individuals, especially in nursing homes. Such care involves facilitating independent living, supporting social participation within nursing home settings, and preventing unintentional injuries such as falls. To effectively implement this, caregivers need to thoroughly understand the daily living activities of elderly people and to improve their living environments. The purpose of this study is to develop a system that can assist in planning residents' daily living care through automatically summarizing the daily activities in their rooms using depth cameras that respect privacy. The developed system consists of a function for extracting how elderly individuals use daily objects and another function for classifying behaviors based on the object use activities through hierarchical clustering. This system allows caregivers to understand the daily routines of the residents without predefining behaviors to be identified. To evaluate the effectiveness of the proposed method, the authors applied the method to analyzing 9 days’ worth of activities of an 87-year-old female resident in a nursing home. The experimental results demonstrate that the system was able to detect abnormal behaviors such as the repeated, unnatural use of drawers, without any predefined criteria for abnormal behaviors. The caregivers confirmed the utility of the system in summarizing daily behavior patterns and automatically detecting abnormal behaviors typically seen in elderly individuals with dementia.