Multimodal analysis of body sensor network data streams for real-time healthcare

Fundamental advances in low power circuits, wireless communication, physiological sensor design, and multimedia stream processing, have led to the deployment of body sensor networks for the real-time monitoring of individual health in diverse settings. In this paper we will present a summary of the state-of-the-art in the design and development of aggregation, processing, analysis, and retrieval techniques for body sensor network data streams. In particular, we will focus on multi-modal stream analysis techniques, in distributed and resource constrained environments, for effective real-time healthcare applications. We will describe the associated research challenges ranging from designing novel applications and mining algorithms to systems issues of resource-adaptation, reliability etc., and the intersection of these. We will also present practical deployments and emerging applications of body sensor networks both in individual healthcare as well as in applications for large-scale public health tracking of communities. We will conclude with a summary of open challenges in the field.