Analyzing Eye Movement Complexity in Virtual Reality Environments

This chapter advances the analysis of gaze dynamics by employing Multiscale Entropy (MSE) to evaluate 5020 binocular eye movement recordings from 407 college-aged participants. Utilizing the comprehensive GazeBaseVR dataset, this study investigates the complexity of user interactions across a variety of virtual reality (VR) tasks such as vergence, smooth pursuit, video viewing, reading, and random saccades. The data, collected at 250 Hz using an ET-enabled VR headset, provides a robust foundation for understanding the predictability and complexity of gaze patterns. By incorporating a longitudinal perspective from recordings taken up to six times over a 26-month period, this analysis deepens our understanding of eye movement behavior in VR environments. This chapter highlights the potential of MSE in crafting more intuitive and immersive VR interfaces, thereby enhancing user experience. Recent advancements and additional references have been included to discuss the evolving role of MSE in optimizing VR technology for personalized and comfortable user interactions.