Study of emotion recognition under stress based on physiological signals by PSO-kNN method / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 79-83, 2013.
Artículo
en Chino
| WPRIM
| ID: wpr-342878
ABSTRACT
In this paper, experiments were designed for inducing neutral, terrified, excited, annoying emotions, and also low, middle, high, three levels of tension emotions of stress state, respectively. Based on the multi physiological signals generated by the subjects in emotions, such as heart rate and respiration rate and so on, we extracted features from these data which had been eliminated the baseline. Then the Particle Swarm Optimization method was adopted to optimize the features selection from the features of multi physiological signals, and combined with k-Nearest Neighbor algorithm, different emotions and varying degree tensions were classified. The result shows that the classification accuracy of the kNN method with SPO and baseline eliminated is better than the traditional kNN method.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Estrés Psicológico
/
Algoritmos
/
Investigación Conductal
/
Emociones
/
Métodos
Límite:
Humanos
Idioma:
Chino
Revista:
Chinese Journal of Medical Instrumentation
Año:
2013
Tipo del documento:
Artículo
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