Emotion Recognition Based on Multiple Physiological Signals / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 283-287, 2020.
Artículo
en Chino
| WPRIM
| ID: wpr-828203
ABSTRACT
Emotion is a series of reactions triggered by a specific object or situation that affects a person's physiological state and can, therefore, be identified by physiological signals. This paper proposes an emotion recognition model. Extracted the features of physiological signals such as photoplethysmography, galvanic skin response, respiration amplitude, and skin temperature. The SVM-RFE-CBR(Recursive Feature Elimination-Correlation Bias Reduction-Support Vector Machine) algorithm was performed to select features and support vector machines for classification. Finally, the model was implemented on the DEAP dataset for an emotion recognition experiment. In the rating scale of valence, arousal, and dominance, the accuracy rates of 73.5%, 81.3%, and 76.1% were obtained respectively. The result shows that emotional recognition can be effectively performed by combining a variety of physiological signals.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Nivel de Alerta
/
Fotopletismografía
/
Emociones
/
Máquina de Vectores de Soporte
/
Respuesta Galvánica de la Piel
Límite:
Humanos
Idioma:
Chino
Revista:
Chinese Journal of Medical Instrumentation
Año:
2020
Tipo del documento:
Artículo
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