Driving Stress Detection Using Multimodal Convolutional Neural Networks with Nonlinear Representation of Short-Term Physiological Signals.

Lee, Jaewon; Lee, Hyeonjeong; Shin, Miyoung

Lee, Jaewon; Lee, Hyeonjeong; Shin, Miyoung.

Afiliação

Lee J; Bio-Intelligence & Data Mining Laboratory, School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.
Lee H; Bio-Intelligence & Data Mining Laboratory, School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.
Shin M; Bio-Intelligence & Data Mining Laboratory, School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.

Sensors (Basel) ; 21(7)2021 Mar 30.

Article em En | MEDLINE | ID: mdl-33808147

Assuntos

Condução de Veículo; Redes Neurais de Computação; Acidentes de Trânsito; Resposta Galvânica da Pele; Frequência Cardíaca

Palavras-chave

convolutional neural network (CNN); deep learning; galvanic skin response (GSR); heart rate (HR); physiological signals; recurrence plot (RP); stress detection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Condução de Veículo / Redes Neurais de Computação Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article

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