Date of Award

6-1-2009

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science

First Advisor

Kimberly Newman, Ph.D.

Second Advisor

Cynthia McRae, Ph.D.

Third Advisor

Roger Salters, Ph.D.

Fourth Advisor

Mohammad Mahoor, Ph.D.

Keywords

Monte Carlo Simulation, Probabilistic analysis, Wireless body area sensor Network

Abstract

Wireless Body Area Sensor Networks (WBASN) is an emerging technology which utilizes wireless sensors to implement real-time wearable health monitoring of patients to enhance independent living. These sensors can be worn externally to monitor multiple bio-parameters (such as blood oxygen saturation (SpO2), blood pressure and heart activity) of multiple patients at a central location in the hospital.

In health monitoring, the loss of critical or emergency information is a serious issue so there is a concern for quality of service which needs to be addressed. It is important to have an estimate of the time the first node will fail in order to replace or recharge the battery. A common type of failure happens when a node runs out of energy and shuts down.

In this work, Monte Carlo simulation is used to determine the lifetime of WBASN. The lifetime of the WBASN is defined in this work as the duration of time until the first sensor failure due to battery depletion. A parametric model of the health care network is created with sets of random input distributions. Probabilistic analysis is used to determine the timing and distributions of nodes' failures in the health monitoring network.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Frank Agyei-Ntim

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

92 p.

Discipline

Electrical engineering

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