Login | Register

Signal processing approaches to diagnosis of esophageal motility disorders

Title:

Signal processing approaches to diagnosis of esophageal motility disorders

Najmabadi, Mani (2008) Signal processing approaches to diagnosis of esophageal motility disorders. Masters thesis, Concordia University.

[thumbnail of MR45496.pdf]
Preview
Text (application/pdf)
MR45496.pdf - Accepted Version
1MB

Abstract

Esophageal Motility Disorders (EGMDs) are a group of abnormalities characterized by the muscular dysfunction of the esophagus in the transportation of food from the oral cavity to the stomach. EGMDs typically cause chronic problems and affect a vast and ever-increasing number of the global population. The diagnosis of EGMDs mainly relies on a key test presently used to study the esophagus motility, known as esophageal manometry (EGM). EGM involves pressure measurements inside the esophagus, which provide information pertaining to its contractions. The diagnosis process is mainly based on visual inspection of the EGM test results to find certain characteristics of the manometric patterns. There are several factors that make such inspection tedious. For instance, manometry test results are often contaminated with a considerable amount of noise, (e.g. noise from external environment) and artifacts, (e.g. respiration artifacts) leading to a longer and more complex diagnosis process. As such, the diagnosis based on visual inspection is prone to human error and demands extensive amount of expert's time. This thesis introduces new signal processing approaches to provide an accurate means for the diagnosis of EGMDs as well as to reduce the amount of time spent on the diagnosis process. Specifically, a new technique known as wavelet decomposition (WD) is applied to the filtering of the EGM data. A nonlinear pulse detection technique (NPDT) is applied to the de-noised data leading to extraction of diagnostically important information i.e. esophageal pulses. Such information is used to generate a model using a statistical pulse modeling (SPM) technique, which can classify the EGM patterns. The proposed approaches are applied to the EGM data of 20 patients and compared with those from existing techniques. Such comparisons illustrate the advantages of the proposed approaches in terms of accuracy and efficiency. As part of this thesis, a new circuit-based approach is proposed for the treatment of Gastroesophageal Reflux Disease (GERD), i.e. the most prevalent disease caused by EGMDs. The objective is to provide a framework for further research towards the implementation of the proposed approach for GERD treatment.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Najmabadi, Mani
Pagination:xvi, 96 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:2008
Thesis Supervisor(s):Devabhaktuni, Vijay and Sawan, Mohamad
Identification Number:LE 3 C66E44M 2008 N35
ID Code:975952
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:17
Last Modified:13 Jul 2020 20:09
Related URLs:
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top