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Neighbourhood counting for activity detection from time series sensor data

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2 Author(s)
Xin Hong ; Sch. of Comput. & Math., Univ. of Ulster, Newtownabbey, UK ; Nugent, C.D.

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.

Published in:

Information Technology and Applications in Biomedicine (ITAB), 2010 10th IEEE International Conference on

Date of Conference:

3-5 Nov. 2010