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Convolutional neural network based on recurrence plot for EEG recognition

التفاصيل البيبلوغرافية
العنوان: Convolutional neural network based on recurrence plot for EEG recognition
المؤلفون: Chongqing Hao, Ruiqi Wang, Mengyu Li, Chao Ma, Qing Cai, Zhongke Gao
المصدر: Chaos: An Interdisciplinary Journal of Nonlinear Science. 31:123120
بيانات النشر: AIP Publishing, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Epilepsy, Seizures, Applied Mathematics, Brain, Humans, General Physics and Astronomy, Electroencephalography, Statistical and Nonlinear Physics, Neural Networks, Computer, Mathematical Physics
الوصف: Electroencephalogram (EEG) is a typical physiological signal. The classification of EEG signals is of great significance to human beings. Combining recurrence plot and convolutional neural network (CNN), we develop a novel method for classifying EEG signals. We select two typical EEG signals, namely, epileptic EEG and fatigue driving EEG, to verify the effectiveness of our method. We construct recurrence plots from EEG signals. Then, we build a CNN framework to classify the EEG signals under different brain states. For the classification of epileptic EEG signals, we design three different experiments to evaluate the performance of our method. The results suggest that the proposed framework can accurately distinguish the normal state and the seizure state of epilepsy. Similarly, for the classification of fatigue driving EEG signals, the method also has a good classification accuracy. In addition, we compare with the existing methods, and the results show that our method can significantly improve the detection results.
تدمد: 1089-7682
1054-1500
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c870a9a7d1ebc0bcefd86a076237ee2
https://doi.org/10.1063/5.0062242
رقم الأكسشن: edsair.doi.dedup.....8c870a9a7d1ebc0bcefd86a076237ee2
قاعدة البيانات: OpenAIRE
الوصف
تدمد:10897682
10541500