test Browse by Author Names Browse by Titles of Works Browse by Subjects of Works Browse by Issue Dates of Works
       

Advanced Search
Home   
 
Browse   
Communities
& Collections
  
Issue Date   
Author   
Title   
Subject   
 
Sign on to:   
Receive email
updates
  
My Account
authorized users
  
Edit Profile   
 
Help   
About T-Space   

T-Space at The University of Toronto Libraries >
School of Graduate Studies - Theses >
Master >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/17234

Title: Application of Singular Spectrum-based Change-point Analysis to EMG Event Detection
Authors: Vaisman, Lev
Advisor: Popovic, Milos R.
Department: Biomedical Engineering
Keywords: EMG signal processing
change-point detection
singular spectrum analysis-based detection
Issue Date: 26-Feb-2009
Abstract: Electromyogram (EMG) is an established tool to study operation of neuromuscular systems. In analysing EMG signals, accurate detection of the movement-related events in the signal is frequently necessary. I explored the application of change-point detection algorithm proposed by Moskvina et. al., 2003 to EMG event detection, and evaluated the technique’s performance comparing it to two common threshold-based event detection methods and to the visual estimates of the EMG events performed by trained practitioners in the field. The algorithm was implemented in MATLAB and applied to EMG segments recorded from wrist and trunk muscles. The quality and frequency of successful detection were assessed for all methods, using the average visual estimate as the baseline, against which techniques were evaluated. The application showed that the change-point detection can successfully locate multiple changes in the EMG signal, but the maximum value of the detection statistic did not always identify the muscle activation onset.
URI: http://hdl.handle.net/1807/17234
Appears in Collections:Master
Institute of Biomaterials and Biomedical Engineering - Master theses

Files in This Item:

File Description SizeFormat
Vaisman_Lev_200807_MASc_thesis.pdf873.13 kBAdobe PDF
View/Open

Items in T-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

uoft