Flinders University Flinders Academic Commons
 

Flinders Academic Commons >
Flinders Digital Archive >
Science and Engineering >
Computer Science, Engineering and Mathematics  >
Computer Science, Engineering and Mathematics - Collected Works >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/25839

Title: Principal components of recurrence quantification analysis of EMG
Authors: Mewett, David
Reynolds, Karen Jane
Nazeran, Homer
Keywords: Electromyograms
Principal component analysis
Feature extraction
Signal processing
Issue Date: 2001
Publisher: Institute of Electrical and Electronics Engineers Computer Society (IEEE Publishing)
Citation: Mewett, D., Reynolds, K. and Nazeran, H. 2001. Principal components of recurrence quantification analysis of EMG. 2001 Proceedings of the 23rd Annual EMBS International Conference, vol. 2, 1592 - 1595.
Abstract: A nonlinear dynamical signal analysis technique, recurrence quantification analysis (RQA), was applied to surface electromyograms (EMG) recorded during a series of isometric contractions. None of the ten RQA features calculated adequately related the EMG to the force level so principal components analysis was applied to combine these features into a lower number of variables. Linear regression of the first principal component gave similar lines for each subject. However, the error was too great for these lines to be used in predicting force from the principal component.
URI: http://hdl.handle.net/2328/25839
ISSN: 1094-687X
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

Files in This Item:

File Description SizeFormat
Mewett Principal.pdf381.27 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback