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Principal Components of Recurrence Quantification Analysis of EMG
| Content Provider | Semantic Scholar |
|---|---|
| Author | David, Timothy Reynolds, Karen Jane Nazeran, H. |
| Copyright Year | 2001 |
| Abstract | Abstracr-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 EMC 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://dspace.flinders.edu.au/xmlui/bitstream/handle/2328/25839/Mewett%20Principal.pdf;jsessionid=3DC3C1EE118F9F9C67BDECF24A64C6E1?sequence=1 |
| Alternate Webpage(s) | http://www.dtic.mil/dtic/tr/fulltext/u2/a410708.pdf |
| Alternate Webpage(s) | http://www.dtic.mil/get-tr-doc/pdf?AD=ADA410708 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | ER membrane protein complex Electromyography Isometric Contraction Isometric projection Nonlinear system Principal component analysis Quantitation Recurrence quantification analysis Recurrent Malignant Neoplasm Signal processing |
| Content Type | Text |
| Resource Type | Article |
