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. © 2009 Elsevier Ltd. All rights reserved.

Publication status:: Published

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APA Style

Wu, D., Warwick, K., Ma, Z., Burgess, J., Pan, S., & Aziz, T. (2010). Prediction of Parkinson's disease tremor onset using radial basis function neural networks. EXPERT SYSTEMS WITH APPLICATIONS, 37(4), 2923–2928.

MLA Style

Wu, D., et al. “Prediction of Parkinson's Disease Tremor Onset Using Radial Basis Function Neural Networks.” EXPERT SYSTEMS WITH APPLICATIONS, vol. 37, no. 4, 2010, pp. 2923–28.

Chicago Style

Wu, D, K Warwick, Z Ma, J Burgess, S Pan, and T Aziz. 2010. “Prediction of Parkinson's Disease Tremor Onset Using Radial Basis Function Neural Networks.” EXPERT SYSTEMS WITH APPLICATIONS 37 (4): 2923–28.
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Publisher copy:: 10.1016/j.eswa.2009.09.045

Authors

+ Wu, D More by this author

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+ Warwick, K More by this author

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+ Ma, Z More by this author

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+ Burgess, J More by this author

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+ Pan, S More by this author

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Journal:: EXPERT SYSTEMS WITH APPLICATIONS More from this journal
Volume:: 37
Issue:: 4
Pages:: 2923-2928
Publication date:: 2010-04-01
DOI:: 10.1016/j.eswa.2009.09.045
ISSN:: 0957-4174

Language:: English
Keywords:: Deep brain implantation

Parkinson's disease

Radial basis function neural network
Pubs id:: pubs:149213
UUID:: uuid:798b0806-691f-44b7-b10c-4b0672cd823e
Local pid:: pubs:149213
Source identifiers:: 149213
Deposit date:: 2012-12-19

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Copyright date:: 2010

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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