Study on Feature Selection Methods for Depression Detection Using Three-Electrode EEG Data.

Cai, Hanshu; Chen, Yunfei; Han, Jiashuo; Zhang, Xiangzi; Hu, Bin

Cai, Hanshu; Chen, Yunfei; Han, Jiashuo; Zhang, Xiangzi; Hu, Bin.

Afiliação

Cai H; School of Information Science and Engineering, Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou University, Lanzhou, 730000, China.
Chen Y; School of Information Science and Engineering, Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou University, Lanzhou, 730000, China.
Han J; School of Information Science and Engineering, Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou University, Lanzhou, 730000, China.
Zhang X; School of Information Science and Engineering, Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou University, Lanzhou, 730000, China.
Hu B; School of Information Science and Engineering, Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou University, Lanzhou, 730000, China. bh@lzu.edu.cn.

Interdiscip Sci ; 10(3): 558-565, 2018 Sep.

Article em En | MEDLINE | ID: mdl-29728983

Assuntos

Algoritmos; Depressão/diagnóstico; Eletroencefalografia; Eletrodos; Entropia; Humanos; Máquina de Vetores de Suporte

Palavras-chave

Depressive diagnosis; EEG; Feature selection

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Depressão / Eletroencefalografia Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Interdiscip Sci Assunto da revista: BIOLOGIA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google