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JACIII Vol.23 No.3 pp. 528-535
doi: 10.20965/jaciii.2019.p0528
(2019)

Paper:

A Fuzzy Inference-Based Spiking Neural Network for Behavior Estimation in Elderly Health Care System

Shuai Shao and Naoyuki Kubota

Graduate School of Systems Design, Tokyo Metropolitan University
6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

Received:
November 29, 2018
Accepted:
December 27, 2018
Published:
May 20, 2019
Keywords:
population aging, sensor network, information structure space, spiking neural network, fuzzy inference system
Abstract
A Fuzzy Inference-Based Spiking Neural Network for Behavior Estimation in Elderly Health Care System

Behavior estimation system in bathroom

In recent years, population aging has become an important social issue. We hope to achieve an elderly health care system through technical means. In this study, we developed an elderly health care system. We chose to use environmental sensors to estimate the behavior of older adults. We found that traditional methods have difficulty solving the problem of excessive indoor environmental differences in different households. Therefore, we provide a fuzzy spike neural network. By modifying the sensitivity of input using a fuzzy inference system, we can solve the problem without additional training. In the experiment, we used temperature and humidity data to make an estimation of behavior in the bathroom. The results show that the system can estimate behavior with 97% accuracy and 78% sensitivity.

Cite this article as:
S. Shao and N. Kubota, “A Fuzzy Inference-Based Spiking Neural Network for Behavior Estimation in Elderly Health Care System,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.3, pp. 528-535, 2019.
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Last updated on Nov. 18, 2019