The importance of Ambient Assisted Living (AAL) systems as a new paradigm to provide assistance to independent older adults at home is constantly growing. In this context, one of the most demanded feature is the possibility to promptly alert caregivers if an anomaly -e.g., a fall or a domestic accident - occurs. However, it is particularly difficult to monitor situations where the subject performs activities that do not involve motion (e.g., "sleeping", "watching TV"). In such cases, there is the need to understand whether the behavior of the person at home has a normal flow or if, for example, it is due to an illness that the monitoring system might not distinguish from other activities. In this work, we deepened the concept of home inactivity and we report a statistical survey study to identify the most relevant variables (observable set) that should be considered while designing an efficient AAL system.

Understanding home inactivity for human behavior anomaly detection

A. Masciadri;S. Comai;F. Salice
2019-01-01

Abstract

The importance of Ambient Assisted Living (AAL) systems as a new paradigm to provide assistance to independent older adults at home is constantly growing. In this context, one of the most demanded feature is the possibility to promptly alert caregivers if an anomaly -e.g., a fall or a domestic accident - occurs. However, it is particularly difficult to monitor situations where the subject performs activities that do not involve motion (e.g., "sleeping", "watching TV"). In such cases, there is the need to understand whether the behavior of the person at home has a normal flow or if, for example, it is due to an illness that the monitoring system might not distinguish from other activities. In this work, we deepened the concept of home inactivity and we report a statistical survey study to identify the most relevant variables (observable set) that should be considered while designing an efficient AAL system.
Proceedings of the 5th EAI International Conference on Smart Objects and Technologies for Social Good, GoodTechs 2019
978-1-4503-6261-0
Human behavior
Anomaly detection
Ambient assisted living
Home inactivity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1128462
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