Analysis of Relationship between Natural Standing Behavior of Elderly People and a Class of Standing Aids in a Living Space

Abstract

As the world’s population ages, technology-based support for the elderly is becoming increasingly important. This study analyzes the relationship between natural standing behavior measured in a living space of elderly people and the classes of standing aids, as well as the physical and cognitive abilities contributing to household fall injury prevention. In total, 24 elderly standing behaviors from chairs, sofas, and nursing beds recorded in an RGB-D elderly behavior library were analyzed. The differences in standing behavior were analyzed by focusing on intrinsic and common standing aid characteristics among various seat types, including armrests of chairs or sofas and nursing bed handrails. The standing behaviors were categorized into two types: behaviors while leaning the trunk forward without using an armrest as a standing aid and those without leaning the trunk forward by using an arrest or handrail as a standing aid. The standing behavior clusters were distributed in a two-dimensional map based on the seat type rather than the physical or cognitive abilities. Therefore, to reduce the risk of falling, it would be necessary to implement a seat type that the elderly can unconsciously and naturally use as a standing aid even with impaired physical and cognitive abilities.

Assessing Handrail-Use Behavior during Stair Ascent or Descent Using Ambient Sensing Technology

“…We previously developed an “elderly behavior library” [ 17 , 18 , 19 ], which includes RGB-D videos, that showed the natural behavior of elderly people when using consumer products that were placed in their residences or residential facilities. We then analyzed the relationship between the natural standing behavior of elderly people and classes of standing aids as well as the physical and cognitive abilities that help prevent injury due to falling indoors [ 20 , 21 ]. Thus, the integration of ambient sensing into IoT devices has helped to record the daily activities of elderly people in their homes in a non-invasive manner and evaluate their physical functions according to the recorded patterns.…”

A Novel Image Recognition-Based Assessment System for Elderly Independent Living Ability and Its Applications

“…A crucial element in gauging the life quality of elderly citizens is the assessment of their ability to live independently. This evaluation holds immense importance not only in the sphere of elderly care but also in the drafting of related policies [12][13][14]. In the light of remarkable advancements in computer vision and artificial intelligence over the past decades, there has been a growing interest in image recognition-based independent living ability assessment systems for the elderly in the associated research field [15][16][17][18][19][20].…”