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Neighbourhood Counting for Activity Detection from Time Series Sensor Data

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

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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DOI: 10.1109/ITAB.2010.5687818

Abstract

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
ID Code:17317
Deposited By:Dr Xin Hong
Deposited On:07 Apr 2011 15:32
Last Modified:18 Feb 2013 12:26

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