Epileptic prediction using spatiotemporal information combined with optimal features strategy on EEG.

Zhong, Lisha; Wan, Jiangzhong; Yi, Fangji; He, Shuling; Wu, Jia; Huang, Zhiwei; Lu, Yi; Yang, Jiazhang; Li, Zhangyong

Zhong, Lisha; Wan, Jiangzhong; Yi, Fangji; He, Shuling; Wu, Jia; Huang, Zhiwei; Lu, Yi; Yang, Jiazhang; Li, Zhangyong.

Afiliación

Zhong L; School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Wan J; School of Medical Information and Engineering, Southwest Medical University, Luzhou, Sichuan, China.
Yi F; School of Medical Information and Engineering, Southwest Medical University, Luzhou, Sichuan, China.
He S; Research Center of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Wu J; School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Huang Z; School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Lu Y; School of Medical Information and Engineering, Southwest Medical University, Luzhou, Sichuan, China.
Yang J; School of Medical Information and Engineering, Southwest Medical University, Luzhou, Sichuan, China.
Li Z; School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.

Front Neurosci ; 17: 1174005, 2023.

Article en En | MEDLINE | ID: mdl-37081931

Palabras clave

EEG; brain network; epilepsy; fuzzy entropy; power spectral density; spatiotemporal features

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Neurosci Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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