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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Arjunan, S.P. Kumar, D.K. |
| Copyright Year | 2007 |
| Description | Author affiliation: RMIT Univ., Melbourne (Arjunan, S.P.; Kumar, D.K.) |
| Abstract | The paper reports the use of fractal theory and fractal dimension to study the non-linear properties of surface electromyogram (sEMG) and to use these properties to classify subtle hand actions. The paper reports identifying a new feature of the fractal dimension, the bias that has been found to be useful in modelling the muscle activity and of sEMG. Experimental results demonstrate that the feature set consisting of bias values and fractal dimension of the recordings is suitable for classification of sEMG against the different hand gestures. The scatter plots demonstrate the presence of simple relationships of these features against the four hand gestures. The results indicate that there is small inter-experimental variation but large inter-subject variation. This may be due to differences in the size and shape of muscles for different subjects. The possible applications of this research include use in developing prosthetic hands, controlling machines and computers. |
| Starting Page | 1961 |
| Ending Page | 1964 |
| File Size | 223585 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424407873 |
| ISSN | 1557170X |
| DOI | 10.1109/IEMBS.2007.4352702 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-22 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electromyography Fractals Muscles Signal processing Scattering Shape Application software Prosthetic hand Neurons Recruitment |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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