Abstract
This paper investigates the combined use of ambient and wearable sensing for inferring changes in patient behaviour patterns. It has been demonstrated that with the use of wearable and blob based ambient sensors, it is possible to develop an effective visualization framework allowing the observation of daily activities in a homecare environment. An effective behaviour modelling method based on Hidden Markov Models (HMMs) has been proposed for highlighting changes in activity patterns. This allows for the representation of sequences in a similarity space that can be used for clustering or data-exploration.
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© 2007 International Federation for Medical and Biological Engineering
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Atallah, L. et al. (2007). Behaviour Profiling with Ambient and Wearable Sensing. In: Leonhardt, S., Falck, T., Mähönen, P. (eds) 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007). IFMBE Proceedings, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70994-7_23
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DOI: https://doi.org/10.1007/978-3-540-70994-7_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70993-0
Online ISBN: 978-3-540-70994-7
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