An activity monitoring system allows many applications to assist in care giving for elderly in their homes. In this paper we present a wireless sensor network for unintrusive observations in the home and show the potential of generative and discriminative models for recognizing activities from such observations. Through a large number of experiments using four real world datasets we show the effectiveness of the generative hidden Markov model and the discriminative conditional random fields in activity recognition. © 2010 The Author(s).
CITATION STYLE
Van Kasteren, T. L. M., Englebienne, G., & Kröse, B. J. A. (2010). An activity monitoring system for elderly care using generative and discriminative models. Personal and Ubiquitous Computing, 14(6), 489–498. https://doi.org/10.1007/s00779-009-0277-9
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