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