A multi-modal sensor infrastructure for healthcare in a residential environment

• Main Authors: Woznowski, Przemyslaw, Fafoutis, Xenofon, Song, Terence, Sion Hannuna, Camplani, Massimo, Lili Tao, Paiement, Adeline, Mellios, Evangelos, Mo Haghighi, Ni Zhu, Hilton, Geoffrey, Damen, Dima, Burghardt, Tilo, Mirmehdi, Majid, Piechocki, Robert, Kaleshi, Dritan, Craddock, Ian
• Format: Conference Proceeding
• Language: English
• Subjects: Ambient Assisted Living; Ambient Intelligence; Biomedical monitoring; Cameras; eHealth; Internet of Things; Logic gates; Monitoring; Sensors; Wireless communication; Wireless sensor networks
• ISSN: 2164-7038
• DOI: 10.1109/ICCW.2015.7247190

Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.