Structural action recognition in body sensor networks: distributed classification based on string matching

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life-logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorit...

• Type: Journal
• Year: 2010
• Where: TITB
• Authors: Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari
• Keywords: Education, Motion Templates, Off-the-shelf Inertial Sensor, Sensor Node, TITB 2010