Graph-Based EEG Analysis for Parkinson’s Disease Classification: A Residual Neural Network Approach-Reference-Cited by-同舟云学术

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Graph-Based EEG Analysis for Parkinson’s Disease Classification: A Residual Neural Network Approach

Published:2024-06-30 Issue: Volume: Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Santos Lucas de O.¹,Medeiros Aldísio G.²,Rego Paulo A. L.³,Filho Pedro P. Rebouças⁴

Affiliation:

1. Federal University of Ceara, Brazil,Electrical Engineering (PPGEE),Fortaleza,Brazil

2. Federal University of Ceara, Brazil,Fortaleza,Brazil

3. Federal University of Ceará, Brazil,Postgraduate in Computer Science,Fortaleza,Brazil

4. Federal Institute of Ceara, Brazil,Fortaleza,Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10651047.pdf?arnumber=10651047

Reference16 articles.

1. Understanding of a convolutional neural network

2. Parkinson’s Disease Detection from Resting-State EEG Signals Using Common Spatial Pattern, Entropy, and Machine Learning Techniques

3. Linear predictive coding distinguishes spectral EEG features of Parkinson's disease

4. A Hybrid Deep Spatiotemporal Attention‐Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals

5. Attention Classification Based on Biosignals during Standard Cognitive Tasks for Occupational Domains

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