| KEYWORD |
GR-09 - GRAphics and INtelligent Systems - GRAINS
Investigating the effect of habituation on susceptibility to cybersickness in Virtual Reality
keywords VIRTUAL AND AUGMENTED REALITY
Reference persons FABRIZIO LAMBERTI
External reference persons DAVIDE CALANDRA
Research Groups GR-09 - GRAphics and INtelligent Systems - GRAINS
Description Cybersickness is a disorder characterized by symptoms like nausea or discomfort, that can happen meanwhile or after using Virtual Reality (VR) . Similarly to motion sickness, it is mainly caused by inconsistency between visual and aural stimuli from the simulated virtual environment and the expected feedback from the vestibular system.
Several mitigation and prevention techniques have been proposed and adopted in many commercial products. However, most of them are highly situational, or require making implementation choices that can have a negative impact on core aspects such immersion, naturalness, and sense of presence.
An approach that is still underexplored but gaining popularity among communities of users is the phenomenon of “habituation to VR”, colloquially known as “VR Legs”. It is known that repeated exposure to VR tends to reduce users' susceptibility to Cybersickness. Various VR users have reported that they have been able to develop VR Legs through repeated VR sessions of increasing duration and intensity over time. However, there is no study that has verified the existence of this phenomenon, nor are there validated guidelines that, if followed, could provide these theoretical benefits.
The objective of this thesis proposal is therefore to design a “VR Legs development” protocol, based on publicly available applications or on applications created for the purpose, which should allow a user who follows it meticulously to gain the benefits of habituation and reduce susceptibility to Cybersickness. The protocol will then be evaluated through a longitudinal user study to demonstrate its effectiveness and applicability.
References: https://xinreality.com/wiki/VR_legs.
See also http://grains.polito.it/work.php
Deadline 15/01/2025
PROPONI LA TUA CANDIDATURA