Hong, Xin and Nugent, CD (2010) Neighbourhood Counting for Activity Detection from Time Series Sensor Data. In: Proceedings of the 10th International Conference on Information Technology and Applications in Biomedicine, Corfu, Greece. IEEE. 4 pp. [Conference contribution]
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Health status along with assistive support requirements can be assessed by measures of activities of daily living. Advances in pervasive sensing and intelligent reasoning pave a way to monitor, i.e. detect and recognise, activities automatically and unobtrusively. The first task in monitoring activities is to detect when an activity has taken place based on a time series of sensor activation events. Inspired by the concepts of dynamic time warping and neighborhood counting matrix in similarity measures, this paper proposes a novel method to segment streams of sensor events for activity detection. Sensor segments may then be used as inputs to evidential ontology networks of activities for activity recognition.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Smart Environments
|Deposited By:||Dr Xin Hong|
|Deposited On:||07 Apr 2011 15:32|
|Last Modified:||18 Feb 2013 12:26|
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