Enabling technologies for distributed body sensor networks


De Jager, Dirk (2012) Enabling technologies for distributed body sensor networks. University of Southampton, Faculty of Physical and Applied Sciences, Doctoral Thesis , 210pp.

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Description/Abstract

Low Power Wireless Sensor Networks, Preventative Healthcare and Pervasive Systems are set to provide long-term continuous monitoring, diagnosis and care for patients in
the next few years. Distributed forms of these networks are investigated from a holistic point of view. Individual components of these systems including: sensors, software and
hardware implementations are investigated and analysed. Novel sensors are developed for low power capturing of Body Sensor Network (BSN) information to enable long term
use. Software frameworks are designed to enable these technologies to run on low power nodes as well as enabling them to perform evaluation of their data before transmission
into the network. An architecture is designed to enable task distribution to intensive processing from low power nodes. Two forms of distributed BSNs are also developed:
a horizontal network and a vertical network. It is shown that using these two types of networks enables information and task distribution allowing low power sensing nodes
to evaluate information before transmission. These systems have the opportunity to revolutionalise expensive acute episodic care systems of today, but are not currently
being implemented or investigated to the extent that they could. The technological barriers to entry are addressed in this thesis with the investigation and evaluation of
distributed body sensor networks. It is shown that horizontal networks can distribute information eficiently, while vertical networks can distribute processing eficiently.

Item Type: Thesis (Doctoral)
Subjects: R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
ePrint ID: 340622
Date Deposited: 13 Aug 2012 15:36
Last Modified: 27 Mar 2014 20:23
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/340622

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