Collaborative signal processing for action recognition in body sensor networks: A distributed classification algorithm using motion transcripts

Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations

Abstract

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. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN '10
Pages244-255
Number of pages12
DOIs
StatePublished - 2010
Externally publishedYes
Event9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2010 - Stockholm, Sweden
Duration: Apr 12 2010Apr 16 2010

Publication series

NameProceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN '10

Conference

Conference9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2010
Country/TerritorySweden
CityStockholm
Period4/12/104/16/10

Keywords

  • body sensor networks
  • collaborative signal processing
  • distributed classification
  • motion transcripts

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Collaborative signal processing for action recognition in body sensor networks: A distributed classification algorithm using motion transcripts'. Together they form a unique fingerprint.

Cite this