Hybrid Methodology Using Electroencephalogram and Eye-tracking for Virtual Reality Design and Optimization
Résumé
To design virtual reality (VR) applications, while traditional methods
of collecting user feedback have been valuable, they sometimes
fall short in providing a complete understanding of the user experience.
In this study, we explore the use of physiological sensors
to gather objective data in order to enhance VR design and optimization,
alongside traditional feedback methods. By using software
recording, eye-tracking and electroencephalogram (EEG), we
obtained exploitable metrics such as cognitive load, attention, completion
time and inputs handling. We combined them with user
feedback to create a new methodology of controller selection for
a teleoperation and training VR application. Our findings highlight
the potential of incorporating bio-sensors to complement traditional
feedback methods, paving the way for more immersive and effective
VR experiences
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