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. © 2014 Springer International Publishing.
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CITATION STYLE
Katzouris, N., Artikis, A., & Paliouras, G. (2014). Event recognition for unobtrusive assisted living. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8445 LNCS, pp. 475–488). Springer Verlag. https://doi.org/10.1007/978-3-319-07064-3_41
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