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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fairley, J.A. Georgoulas, G. Stylios, C.D. Vachtsevanos, G. Rye, D.B. Bliwise, D.L. |
| Copyright Year | 2011 |
| Description | Author affiliation: NIH NINDS postdoctoral fellow at Emory University School of Medicine Department of Neurology, Atlanta, GA 30322 USA (Fairley, J.A.) || Department of Informatics and Communications Technology, Technological Educational Institution of Epirus, Arta, 47100 Greece (Georgoulas, G.; Stylios, C.D.) || Georgia Institute of Technology, Atlanta, 30332 USA (Vachtsevanos, G.) || Emory University, USA (Rye, D.B.; Bliwise, D.L.) |
| Abstract | The Phasic Electromyographic Metric (PEM) has been recently introduced as a sensitive indicator to differentiate Parkinson's Disease (PD) patients from controls, non-PD patients with a history of Rapid Eye Movement Disorder (RBD) from controls, and PD patients with early and late stage disease. However, PEM assessment through visual inspection is a cumbersome and time consuming process. Therefore, a reliable automated approach is required so as to increase the utilization of PEM as a reliable and efficient clinical tool to track PD progression. In this study an automated method for the detection of PEM is presented, based on the use of signal analysis and pattern recognition techniques. The results are promising indicating that an automatic PEM identification procedure is feasible. |
| Starting Page | 497 |
| Ending Page | 502 |
| File Size | 471493 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457701245 |
| e-ISBN | 9781457701252 |
| DOI | 10.1109/MED.2011.5983202 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-20 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Visualization Feature extraction Electromyography Labeling Leg |
| Content Type | Text |
| Resource Type | Article |
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