Percept-related EEG classification using machine learning approach and features of functional brain connectivity.

Hramov, Alexander E; Maksimenko, Vladimir; Koronovskii, Alexey; Runnova, Anastasiya E; Zhuravlev, Maxim; Pisarchik, Alexander N; Kurths, Jürgen

Hramov, Alexander E; Maksimenko, Vladimir; Koronovskii, Alexey; Runnova, Anastasiya E; Zhuravlev, Maxim; Pisarchik, Alexander N; Kurths, Jürgen.

Afiliação

Hramov AE; Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, The Republic of Tatarstan, Russia.
Maksimenko V; Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, The Republic of Tatarstan, Russia.
Koronovskii A; Faculty of Nonlinear Processes, Saratov State University, 410012 Saratov, Russia.
Runnova AE; Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, The Republic of Tatarstan, Russia.
Zhuravlev M; Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, The Republic of Tatarstan, Russia.
Pisarchik AN; Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, The Republic of Tatarstan, Russia.
Kurths J; Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany.

Chaos ; 29(9): 093110, 2019 Sep.

Article em En | MEDLINE | ID: mdl-31575147

Assuntos

Encéfalo/fisiologia; Eletroencefalografia; Aprendizado de Máquina; Rede Nervosa/fisiologia; Adulto; Feminino; Humanos; Masculino

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Eletroencefalografia / Aprendizado de Máquina / Rede Nervosa Limite: Adult / Female / Humans / Male Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Federação Russa

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