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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.

Original publication

DOI

10.1016/j.eswa.2009.09.045

Type

Journal article

Journal

Expert Systems with Applications

Publication Date

01/04/2010

Volume

37

Pages

2923 - 2928