Journal article
Prediction of Parkinson's disease tremor onset using radial basis function neural networks
- Abstract:
- The possibility of using a radial basis function neural network (RBFNN) to accurately recognise and predict the onset of Parkinson's disease tremors in human subjects is discussed in this paper. The data for training the RBFNN are obtained by means of deep brain electrodes implanted in a Parkinson disease patient's brain. The effectiveness of a RBFNN is initially demonstrated by a real case study.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
- Publisher:
- Elsevier
- Journal:
- Expert Systems with Applications More from this journal
- Volume:
- 37
- Issue:
- 4
- Pages:
- 2923-2928
- Publication date:
- 2010-04-01
- DOI:
- ISSN:
-
0957-4174
- Language:
-
English
- Keywords:
- Subjects:
- UUID:
-
uuid:7d0554c3-0892-45f6-a74d-e5570ce6b4ca
- Local pid:
-
ora:5136
- Deposit date:
-
2011-03-17
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2009
- Notes:
- The full-text of this article is not currently available in ORA, but you may be able to access the article via the publisher copy link on this record page.
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