T-A-MFFNet: Multi-feature fusion network for EEG analysis and driving fatigue detection based on time domain network and attention network.

Peng, Bo; Zhang, Yongqing; Wang, Manqing; Chen, Jun; Gao, Dongrui

Peng, Bo; Zhang, Yongqing; Wang, Manqing; Chen, Jun; Gao, Dongrui.

Afiliación

Peng B; School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
Zhang Y; School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
Wang M; School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China; School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
Chen J; School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
Gao D; School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China; School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: gdr1987@cuit.edu.cn.

Comput Biol Chem ; 104: 107863, 2023 Jun.

Article en En | MEDLINE | ID: mdl-37023639

Asunto(s)

Electroencefalografía; Electroencefalografía/métodos; Factores de Tiempo; Entropía

Palabras clave

Differential entropy; Driving fatigue; Electroencephalogram(EEG); Multi-feature fusion

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Electroencefalografía Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Comput Biol Chem Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

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