Monitoring workspace activities using accelerometers

In this paper, we describe a physical activity classification system using a body sensor network (BSN) consisting of cost sensitive tri-axial accelerometers. We focus on workspace activities (different motions and sitting postures). We use a Naive Bayes classifier and show that we can train the system simply and systematically. For each task, we find a set of features that separate the corresponding activities.