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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rahimi, Fariborz Bee, Carina South, Angela Debicki, Derek Jog, Mandar |
| Copyright Year | 2011 |
| Abstract | Previous, studies have demonstrated variability in the frequency and amplitude in tremor between subjects and between trials in both healthy individuals and those with disease states. However, to date, few studies have examined the composition of tremor. Efficacy of treatment for tremor using techniques such as Botulinum neurotoxin type A (BoNT A) injection may benefit from a better understanding of tremor variability, but more importantly, tremor composition. In the present study, we evaluated tremor variability and composition in 8 participants with either essential tremor or Parkinson disease tremor using kinematic recording methods. Our preliminary findings suggest that while individual patients may have more intra-trial and intra-task variability, overall, task effect was significant only for amplitude of tremor. Composition of tremor varied among patients and the data suggest that tremor composition is complex involving multiple muscle groups. These results may support the value of kinematic assessment methods and the improved understanding of tremor composition in the management of tremor. |
| Starting Page | 470 |
| Ending Page | 473 |
| File Size | 716349 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441211 |
| ISSN | 1557170X |
| e-ISBN | 9781457715891 |
| e-ISBN | 9781424441228 |
| DOI | 10.1109/IEMBS.2011.6090067 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-08-30 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Diseases Kinematics Sensors Muscles Wrist Analysis of variance Frequency measurement |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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