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JRM Vol.29 No.2 pp. 338-345
doi: 10.20965/jrm.2017.p0338
(2017)

Paper:

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Application of Deep Learning to Develop a Safety Confirmation System for the Elderly in a Nursing Home

Masaru Kawakami*, Shogo Toba**, Kohei Fukuda**, Shinya Hori**, Yuki Abe**, and Koichi Ozaki***

*School of Nursing, Jichi Medical University
3311-159 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan

**Graduate School of Engineering, Utsunomiya University
7-1-2 Yoto, Utsunomiya-City, Tochigi 321-8585, Japan

***Faculty of Engineering, Utsunomiya University
7-1-2 Yoto, Utsunomiya-City, Tochigi 321-8585, Japan

Received:
September 20, 2016
Accepted:
February 15, 2017
Published:
April 20, 2017
Creative Commons License
Keywords:
deep learning, non-contact monitoring system, posture discrimination, elderly in nursing home
Abstract
Fall accident prevention is one of the most important issues in elderly care settings. To prevent an accident, it is necessary to notify caregivers if the elderly person is getting out of bed. We have previously developed a posture discrimination system based on body motions. Herein, we propose a discrimination method by using machine learning to improve the performance of the system. A purpose of this study is to evaluate the proposed method. Elderly people in a nursing home were chosen as subjects in this study. We analyzed the body motion data during bed rest and bed exit of the subjects using the proposed method. These results suggest that it is effective.
The motion detection system

The motion detection system

Cite this article as:
M. Kawakami, S. Toba, K. Fukuda, S. Hori, Y. Abe, and K. Ozaki, “Application of Deep Learning to Develop a Safety Confirmation System for the Elderly in a Nursing Home,” J. Robot. Mechatron., Vol.29 No.2, pp. 338-345, 2017.
Data files:
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Last updated on Apr. 22, 2024