Addressing Context Awareness Techniques in Body Sensor Networks

Abstract

Context awareness in Body Sensor Networks (BSNs) has the significance of associating physiological user activity and environment to the sensed signals of the user. The context information derived in 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 issues of context-aware sensing in BSNs, along with a comparison of different techniques for deducing context awareness, namely, Artificial Neural Networks, Bayesian Networks, and Hidden Markov Models.