Your browser doesn't support javascript.
loading
An exploratory study of the effect of age and gender on face scanning during affect recognition in immersive virtual reality.
González-Gualda, Luz M; Vicente-Querol, Miguel A; García, Arturo S; Molina, José P; Latorre, José M; Fernández-Sotos, Patricia; Fernández-Caballero, Antonio.
Afiliación
  • González-Gualda LM; Servicio de Salud de Castilla-La Mancha, Complejo Hospitalario Universitario de Albacete, Servicio de Salud Mental, 02004, Albacete, Spain.
  • Vicente-Querol MA; Neurocognition and Emotion Unit, Instituto de Investigación en Informática de Albacete, 02071, Albacete, Spain.
  • García AS; Neurocognition and Emotion Unit, Instituto de Investigación en Informática de Albacete, 02071, Albacete, Spain.
  • Molina JP; Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071, Albacete, Spain.
  • Latorre JM; Neurocognition and Emotion Unit, Instituto de Investigación en Informática de Albacete, 02071, Albacete, Spain.
  • Fernández-Sotos P; Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071, Albacete, Spain.
  • Fernández-Caballero A; Departmento de Psicología, Universidad de Castilla-La Mancha, 02071, Albacete, Spain.
Sci Rep ; 14(1): 5553, 2024 03 06.
Article en En | MEDLINE | ID: mdl-38448515
ABSTRACT
A person with impaired emotion recognition is not able to correctly identify facial expressions represented by other individuals. The aim of the present study is to assess eyes gaze and facial emotion recognition in a healthy population using dynamic avatars in immersive virtual reality (IVR). For the first time, the viewing of each area of interest of the face in IVR is studied by gender and age. This work in healthy people is conducted to assess the future usefulness of IVR in patients with deficits in the recognition of facial expressions. Seventy-four healthy volunteers participated in the study. The materials used were a laptop computer, a game controller, and a head-mounted display. Dynamic virtual faces randomly representing the six basic emotions plus neutral expression were used as stimuli. After the virtual human represented an emotion, a response panel was displayed with the seven possible options. Besides storing the hits and misses, the software program internally divided the faces into different areas of interest (AOIs) and recorded how long participants looked at each AOI. As regards the overall accuracy of the participants' responses, hits decreased from the youngest to the middle-aged and older adults. Also, all three groups spent the highest percentage of time looking at the eyes, but younger adults had the highest percentage. It is also noteworthy that attention to the face compared to the background decreased with age. Moreover, the hits between women and men were remarkably similar and, in fact, there were no statistically significant differences between them. In general, men paid more attention to the eyes than women, but women paid more attention to the forehead and mouth. In contrast to previous work, our study indicates that there are no differences between men and women in facial emotion recognition. Moreover, in line with previous work, the percentage of face viewing time for younger adults is higher than for older adults. However, contrary to earlier studies, older adults look more at the eyes than at the mouth.Consistent with other studies, the eyes are the AOI with the highest percentage of viewing time. For men the most viewed AOI is the eyes for all emotions in both hits and misses. Women look more at the eyes for all emotions, except for joy, fear, and anger on hits. On misses, they look more into the eyes for almost all emotions except surprise and fear.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Realidad Virtual Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: España Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Realidad Virtual Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: España Pais de publicación: Reino Unido