Prediction of Individual User's Dynamic Ranges of EEG Features from Resting-State EEG Data for Evaluating Their Suitability for Passive Brain-Computer Interface Applications.

Cha, Ho-Seung; Han, Chang-Hee; Im, Chang-Hwan

Cha, Ho-Seung; Han, Chang-Hee; Im, Chang-Hwan.

Afiliação

Cha HS; Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
Han CH; Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
Im CH; Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.

Sensors (Basel) ; 20(4)2020 Feb 12.

Article em En | MEDLINE | ID: mdl-32059543

Assuntos

Interfaces Cérebro-Computador; Eletroencefalografia; Adulto; Algoritmos; Feminino; Humanos; Aprendizado de Máquina; Masculino

Palavras-chave

electroencephalography (EEG); interindividual variability; machine learning; passive braincomputer interfaces; resting state EEG

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Eletroencefalografia / Interfaces Cérebro-Computador Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article

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