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

Neural computing & applications, 2020-08, Vol.32 (15), p.10927-10933 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2018 ;The Natural Computing Applications Forum 2018. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-018-3689-5

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Title:
A deep learning approach for Parkinson’s disease diagnosis from EEG signals
Author: Oh, Shu Lih ; Hagiwara, Yuki ; Raghavendra, U. ; Yuvaraj, Rajamanickam ; Arunkumar, N. ; Murugappan, M. ; Acharya, U. Rajendra
Subjects: Artificial Intelligence ; Artificial neural networks ; Brain ; Computational Biology/Bioinformatics ; Computational Science and Engineering ; Computer Science ; Data Mining and Knowledge Discovery ; Deep learning ; Diagnosis ; Electroencephalography ; Image Processing and Computer Vision ; Parkinson's disease ; Probability and Statistics in Computer Science ; S.I. : Computer aided Medical Diagnosis
Is Part Of: Neural computing & applications, 2020-08, Vol.32 (15), p.10927-10933
Description: 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 usually considered for the early diagnosis. In this work, we have used the EEG signals of twenty PD and twenty normal subjects in this study. A thirteen -layer CNN architecture which can overcome the need for the conventional feature representation stages is implemented. The developed model has achieved a promising performance of 88.25% accuracy, 84.71% sensitivity, and 91.77% specificity. The developed classification model is ready to be used on large population before installation of clinical usage.
Publisher: London: Springer London
Language: English
Identifier: ISSN: 0941-0643
EISSN: 1433-3058
DOI: 10.1007/s00521-018-3689-5
Source: ProQuest Central

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

The Natural Computing Applications Forum 2018 ;The Natural Computing Applications Forum 2018. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-018-3689-5

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