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

Open Access
Conference Proceedings
Authors: Martin PszeidaAmir DiniMichael SchneebergerMelanie LengerLucas PalettaSilvia RusseggerSybille ReidlSarah BeranekB.A.MscSandra SchuesslerAlfred HaeusslBscnRobert HartmannMartin SighartSebastian MayerPatricia PapicBeatrix KochHermine FürliMsc

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.

Keywords: Virtual Reality, affective state, eye tracking features, automated recognition

DOI: 10.54941/ahfe1001843

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