Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
388654 | Expert Systems with Applications | 2010 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Defeng Wu, Kevin Warwick, Zi Ma, Jonathan G. Burgess, Song Pan, Tipu Z. Aziz,