Sciweavers

Share
IPSN
2010
Springer

Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using mot

9 years 10 months ago
Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using mot
Body sensor networks are emerging as a promising platform for remote human monitoring. With the aim of extracting bio-kinematic parameters from distributed body-worn sensors, these systems require collaboration of sensor nodes to obtain relevant information from an overwhelmingly large volume of data. Clearly, efficient data reduction techniques and distributed signal processing algorithms are needed. In this paper, we present a data processing technique that constructs motion transcripts from inertial sensors and identifies human movements by taking collaboration between the nodes into consideration. Transcripts of basic motions, called primitives, are built to reduce the complexity of the sensor data. This model leads to a distributed algorithm for segmentation and action recognition. We demonstrate the effectiveness of our framework using data collected from five normal subjects performing ten transitional movements. The results clearly illustrate the effectiveness of our framework...
Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari
Added 13 Oct 2010
Updated 13 Oct 2010
Type Conference
Year 2010
Where IPSN
Authors Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari
Comments (0)
books