Prediction of Parkinson's disease tremor onset using radial basis function neural networks
| Autor: | Kevin Warwick, Song Pan, Defeng Wu, Jonathan George Burgess, Tipu Z. Aziz, Zi Ma |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
medicine.medical_specialty
Parkinson's disease business.industry Physiology General Engineering Disease patient medicine.disease Medical sciences nervous system diseases Computer Science Applications Physical medicine and rehabilitation Artificial Intelligence Radial basis function neural Engineering & allied sciences Medicine Artificial intelligence business Neuroscience |
| Zdroj: | EXPERT SYSTEMS WITH APPLICATIONS. 37(4) |
| ISSN: | 0957-4174 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect