Ir al contenido

Documat


Emotion detection in aging adults through continuous monitoring of electro-dermal activity and heart-rate variability

  • Autores: María Luz Fernández Aguilar, Arturo Martínez Rodrigo Árbol académico, Jose Valeriano Moncho Bogani, Antonio Fernández Caballero Árbol académico, José Miguel Latorre Postigo Árbol académico
  • Localización: Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I / José Manuel Ferrández Vicente (dir. congr.) Árbol académico, José Ramón Álvarez Sánchez (dir. congr.) Árbol académico, Félix de la Paz López (dir. congr.) Árbol académico, Francisco Javier Toledo Moreo (dir. congr.), Hojjat Adeli (dir. congr.), 2019, ISBN 978-3-030-19591-5, págs. 252-261
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • This paper introduces a system composed of hardware, control software, signal processing and classification for the deployment of a wearable with a high ability to discriminate among seven emotional states (neutral, affection, amusement, anger, disgust, fear and sadness).

      The study described in this proposal focuses on comparing the emotional states of young and older people by means of two physiological parameters, namely electro-dermal activity and heart-rate variability, both captured from the wearable. The wearable emotion detection system is trained by eliciting the desired emotions on eighty young (16 to 26 years old) and fifty older adults (aged 60 to 84) through a film mood induction procedure. Seventeen features are calculated on skin conductance response and heart-rate variability data. Then, these features are classified by a support vector machines. State amusement reached a high number of hits (87.4%), whilst affection received the lowest rate of hits (82.5%). The negative emotion with lowest value is anger (82.4%) and the highest is disgust (85.9%).


Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno