Anomaly detection is a crucial issue for people with dementia and their families to live a safe and comfortable life at home. The elderly monitoring system is a promising solution. However, the conventional systems have limitations in detectable anomalies and support actions, which cannot fully cover individual needs. To achieve more person-centered home care for people with dementia, our research group has been studying environmental sensing with IoT. In this paper, using the environmental sensing, we propose a new service that allows individual users to customize definition of anomaly and corresponding actions. Specifically, borrowing a mechanism of context-aware services, we regard every anomaly observed within the house as a context. We then define every care as an action bound to an anomaly context. This achieves the personalized anomaly detection and care. To demonstrate the feasibility, we implement a prototype system and conduct a practical case study.
CITATION STYLE
Tamamizu, K., Tokunaga, S., Saiki, S., Matsumoto, S., Nakamura, M., & Yasuda, K. (2016). Towards person-centered anomaly detection and support system for home dementia care. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9745, pp. 274–285). Springer Verlag. https://doi.org/10.1007/978-3-319-40247-5_28
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