Parkinson’s disease detection and classification using EEG based on deep CNN-LSTM model

Author:

Li Kuan1,Ao Bin1,Wu Xin1,Wen Qing1,Ul Haq Ejaz1,Yin Jianping1

Affiliation:

1. School of Cyberspace Science, Dongguan University of Technology, Dongguan, China

Funder

Characteristic Innovation Projects of Guangdong Colleges and Universities

The Dongguan Science and Technology of Social Development Program

Publisher

Informa UK Limited

Subject

Molecular Biology,Bioengineering,Biotechnology

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures;Sensors;2024-06-19

2. Human Abnormal Activity Prediction of Long Short-Term Memory using CNNs and RNNs in Deep Learning;2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2024-04-04

3. A novel approach for Parkinson’s disease detection using Vold-Kalman order filtering and machine learning algorithms;Neural Computing and Applications;2024-02-27

4. Artificial Intelligence Assisted Classifier’s and Neural Network Based Prediction and Classification of Parkinson’s Disease;2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM);2024-02-21

5. Deep Learning for Parkinson's Disease Detection: An Analytical Study;2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence);2024-01-18

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