A deep learning approach for Parkinson’s disease diagnosis from EEG signals

An automated detection system for Parkinson’s disease (PD) employing the convolutional neural network (CNN) is proposed in this study. PD is characterized by the gradual degradation of motor function in the brain. Since it is related to the brain abnormality, electroencephalogram (EEG) signals are u...

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Veröffentlicht in:	Neural computing & applications Jg. 32; H. 15; S. 10927 - 10933
Hauptverfasser:	Oh, Shu Lih, Hagiwara, Yuki, Raghavendra, U., Yuvaraj, Rajamanickam, Arunkumar, N., Murugappan, M., Acharya, U. Rajendra
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.08.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Artificial neural networks Automation Brain Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Deep learning Diagnosis Disease Dopamine Electroencephalography Engineering Epilepsy Image Processing and Computer Vision Machine learning Medical diagnosis Mental disorders Neural networks Neurons Parkinson's disease Probability and Statistics in Computer Science S.I. : Computer aided Medical Diagnosis Deep learning Computer-aided detection system Convolutional neural network Parkinson’s disease
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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