Human bio-kinematic monitoring with body area networks

Roozbeh Jafari, Hassan Ghasemzadeh, Eric Guenterberg, Vitali Loseu, Sarah Ostadabas

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Body Area Networks (BANs), known as enabling technology for many biomedical applications, are composed of body-worn sensor devices that can provide mobile and continuous monitoring of the human body. This chapter presents an overview of platform design strategies for BANs with applications in physical movement monitoring. First, an introduction to several compelling applications is given, which shows BAN versatility in both medical and recreational fields. Applications are important in the sense that they help in understanding design requirements of the BAN platform. An architecture of the system, including hardware and software components, is then described. It is followed by a description of typical signal processing for movement monitoring applications. While this type of signal processing flow can be generally used in movement monitoring applications, in order to take the most advantage of the system, the signal processing needs to be custom tailored for each individual application. An example of this process is shown based on the Hidden Markov Model (HMM) movement annotation applications. Finally, the chapter is concluded with discussion of possible BAN system optimizations. In particular, it is shown that the energy consumption of the systemcan be reduced by using buffers to decrease the number of transmissions.

Original languageEnglish (US)
Title of host publicationWireless Body Area Networks
Subtitle of host publicationTechnology, Implementation and Applications
PublisherPan Stanford Publishing Pte. Ltd.
Pages75-106
Number of pages32
ISBN (Print)9789814316712
DOIs
StatePublished - Aug 31 2011
Externally publishedYes

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Human bio-kinematic monitoring with body area networks'. Together they form a unique fingerprint.

Cite this