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- Mori Taketoshi
- Department of Life Support Technology, Graduate School of Medicine, The University of Tokyo
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- Komichi Kazuyuki
- Department of Life Support Technology, Graduate School of Medicine, The University of Tokyo
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- Noguchi Hiroshi
- Department of Life Support Technology, Graduate School of Medicine, The University of Tokyo
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- Umeda-Kameyama Yumi
- Department of Geriatrics, Graduate School of Medicine, The University of Tokyo
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- Sanada Hiromi
- Department of Gerontological Nursing, Graduate School of Medicine, The University of Tokyo
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- Akishita Masahiro
- Department of Geriatrics, Graduate School of Medicine, The University of Tokyo
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- Ohe Kazuhiko
- Department of Healthcare Information Systems, Graduate School of Medicine, The University of Tokyo
Bibliographic Information
- Other Title
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- ファイナンス理論を用いた高齢者の居宅見守りシステムにおける異変検出
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Abstract
The need for home monitoring systems for the elderly is growing because the number of the elderly living alone is on the rise. We propose an anomaly detection method in a home monitoring system for the elderly that takes a time-series of the subject’s activity level data captured by simplistic motion sensors as its input. First, the activity level data were classified into four types based on the trend and volatility of the data of 144 elderly people. Second, we then applied financial models that are suitable for each type of data in order to detect anomalies. For example, an underlying asset pricing model was applied to the data that exhibited trend-presence and constant-volatility. Here an anomaly was defined to be a datum that lies outside the 95% confidence interval for the given model. Finally, the feasibility of this method was evaluated by applying it to the data from a nation project on the activity of elderly people.
Journal
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- Journal of Nursing Science and Engineering
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Journal of Nursing Science and Engineering 3 (1), 21-30, 2016
The Society for Nursing Science and Engineering