CNN and LSTM-Based Emotion Charting Using Physiological Signals.

Dar, Muhammad Najam; Akram, Muhammad Usman; Khawaja, Sajid Gul; Pujari, Amit N

Dar, Muhammad Najam; Akram, Muhammad Usman; Khawaja, Sajid Gul; Pujari, Amit N.

Afiliación

Dar MN; Department of Computer and Software Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Akram MU; Department of Computer and Software Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Khawaja SG; Department of Computer and Software Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Pujari AN; School of Engineering and Technology, University of Hertfordshire, Hatfield AL10 9AB, England, UK.

Sensors (Basel) ; 20(16)2020 Aug 14.

Article en En | MEDLINE | ID: mdl-32823807

Asunto(s)

Electrocardiografía; Electroencefalografía; Emociones; Respuesta Galvánica de la Piel; Redes Neurales de la Computación; Nivel de Alerta; Humanos

Palabras clave

ECG; EEG; GSR; convolutional neural network (CNN); deep neural network; emotion recognition; long short-term memory (LSTM); physiological signals

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Electrocardiografía / Electroencefalografía / Emociones / Respuesta Galvánica de la Piel Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article

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