Hybrid Methodology Using Electroencephalogram and Eye-tracking for Virtual Reality Design and Optimization

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.