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D. Gao, M. Madden, M. Schukat, D. Chambers and G. Lyons, “Arrhythmia Identification from ECG Signals with a Neural Network Classifier Based on a Bayesian Framework,” Proceedings of the 24th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, 2004.

has been cited by the following article:

• TITLE: A Survey on Context-Aware Sensing for Body Sensor Networks

  AUTHORS: Barbara T. Korel, Simon G. M. Koo

  KEYWORDS: Context Awareness, Body Sensor Networks, Artificial Neural Networks, Bayesian Networks, Hidden Markov Models

  JOURNAL NAME: Wireless Sensor Network, Vol.2 No.8, August 3, 2010

  ABSTRACT: Context awareness in Body Sensor Networks (BSNs) has the significance of associating physiological user activity and the environment to the sensed signals of the user. The context information derived from a BSN can be used in pervasive healthcare monitoring for relating importance to events and specifically for accurate episode detection. In this paper, we address the issue of context-aware sensing in BSNs, and survey different techniques for deducing context awareness.