Abstract
Developing intelligent systems towards automated clinical monitoring and assistance for the elderly is attracting growing attention. USEFIL is an FP7 project aiming to provide health-care assistance in a smart-home setting. We present the data fusion component of USEFIL which is based on a complex event recognition methodology. In particular, we present our knowledge-driven approach to the detection of Activities of Daily Living (ADL) and functional ability, based on a probabilistic version of the Event Calculus. To investigate the feasibility of our approach, we present an empirical evaluation on synthetic data.
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Katzouris, N., Artikis, A., Paliouras, G. (2014). Event Recognition for Unobtrusive Assisted Living. In: Likas, A., Blekas, K., Kalles, D. (eds) Artificial Intelligence: Methods and Applications. SETN 2014. Lecture Notes in Computer Science(), vol 8445. Springer, Cham. https://doi.org/10.1007/978-3-319-07064-3_41
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DOI: https://doi.org/10.1007/978-3-319-07064-3_41
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