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- W2991590388 abstract "In recent years, the aging of the population has become a critical social issue that plagues developed countries such as Japan. We aim to alleviate the lack of health care for the elderly caused by inadequate caregivers through technical means. This paper develops an elderly health care system based on the information structure space. We chose to use physical sensors to estimate the behavior of older people. We use fuzzy spike neural networks to adapt to differences in different home environments and post-process with state transition diagrams to improve precision. In the experiment, we used the temperature and humidity data to evaluate the behavior of the bathroom. The results show that the system can accurately estimate human behavior with a precision of 79% and a time delay of 1.7 minutes." @default.
- W2991590388 created "2019-12-05" @default.
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- W2991590388 date "2019-10-01" @default.
- W2991590388 modified "2023-09-24" @default.
- W2991590388 title "A Fuzzy Spiking Neural Network with State Transition Diagram for Behavior Estimation in Elderly Health Care System" @default.
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- W2991590388 doi "https://doi.org/10.1109/smc.2019.8914450" @default.
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