Prediction of Parkinson's disease tremor onset using radial basis function neural networks

Authors:
Defeng Wu;Kevin Warwick;Zi Ma;Jonathan G. Burgess;Song Pan;Tipu Z. Aziz
Affiliations:
Automation Research Centre, Dalian Maritime University, China;School of Systems Engineering, University of Reading, UK;Automation Research Centre, Dalian Maritime University, China;School of Systems Engineering, University of Reading, UK;School of Systems Engineering, University of Reading, UK;University Laboratory of Physiology, University of Oxford, UK
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

Citing 9
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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.