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Estimation of Change in Affective State Using Eye Tracking Features from Virtual Reality Technologies

Authors :
Martin Pszeida
Amir Dini
Michael Schneeberger
Melanie Lenger
Lucas Paletta
Silvia Russegger
Sybille Reidl
Sarah Beranek
B.A. .
Msc .
Sandra Schuessler
Alfred Haeussl
Bscn .
Robert Hartmann
Martin Sighart
Sebastian Mayer
Patricia Papic
Beatrix Koch
Hermine Fürli
Source :
Cognitive Computing and Internet of Things.
Publication Year :
2022
Publisher :
AHFE International, 2022.

Abstract

Affective states play a prominent role in the context of human activation and motivation. Immersive VR-based presence provides opportunities to activate elderly people in the context of preferred leisure activities (Häussl et al., 2021) or to apply mindfulness interventions for their cognitive reserve (Paletta et al., 2021). The appropriate design of positively activating content is pivotal for appropriate changes in users’ affective states. The presented study provided insight into the potential of non-invasive VR-based eye tracking for automated estimation of affective state induced by video content, in an explorative pilot study with seven elderly persons living in a nursing home. The results indicate the feasibility of estimating mood change from typical eye movement features, such as, fixation duration and pupil diameter, as a promising future research topic.

Details

ISSN :
27710718
Database :
OpenAIRE
Journal :
Cognitive Computing and Internet of Things
Accession number :
edsair.doi...........d5ef47754d2223bd7e0c6c298b65a9a7