Advances in Multi-Sensor Fusion for Body Sensor Networks: Algorithms, Architectures, and Applications

Posted on December 24, 2016 in Special Issue
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Advances in Multi-Sensor Fusion for Body Sensor Networks: Algorithms, Architectures, and Applications

Sun 15 Jan 2017

Topics appropriate for this special issue include (but are not necessarily limited to):

Data-level algorithms for multi-sensor fusion in BSNs (e.g. Digital Signal Processing, Coordinate Transforms, Kalman Filtering, Independent Component Analysis)
Feature-level algorithms for multi-sensor fusion in BSNs (e.g. Decision Trees, k-Nearest Neighbor, Naive-Bayes networks, Support Vector Machines)
Decision-level algorithms for multi-sensor fusion in BSNs (e.g. Dempster-Shafer theory, Boosting, bagging, plurality and reputation-based voting, stacking, multi-sensor ensemble)
Multi-level algorithms for multi-sensor fusion in BSNs
Hardware/software architectures (autonomic, agent-oriented, etc) for collaborative multi-sensor fusion in BSNs
Multi-sensor fusion applications in BSNs for human activity recognition
Multi-sensor fusion applications in BSNs for sport monitoring
Multi-sensor fusion applications in BSNs for emotion recognition
Multi-sensor fusion applications in BSNs for health care monitoring

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