Sick Moves! Motion Parameters as Indicators of Simulator Sickness.

Area of Science:

• Human-Computer Interaction
• Virtual Reality (VR) Technology
• Biomedical Engineering

Background:

• Simulator sickness is a common issue in virtual reality (VR) that affects user experience.
• Gait parameters offer a potential objective measure for assessing physiological responses to VR environments.
• Understanding the relationship between motion, presence, and simulator sickness is crucial for VR development.

Purpose of the Study:

• To investigate gait parameters as objective indicators for assessing simulator sickness in VR.
• To compare the effects of different camera pose estimation models on simulator sickness and perceived presence.
• To explore a classification approach for predicting simulator sickness using gait parameters.

Main Methods:

• Participants performed motion tasks (walking, balancing, running) in physical reality and two VR conditions (simple vs. optimized pose estimation models).
• Objective gait parameters and subjective measures of simulator sickness and presence were collected and compared across conditions.
• A classification approach was used to analyze non-linear correlations between gait parameters and simulator sickness.

Main Results:

• The optimized pose estimation model significantly reduced simulator sickness and increased perceived presence compared to the simple model.
• Both VR models influenced gait parameters and simulator sickness levels.
• Subjective measures confirmed the benefits of the optimized model for user experience.

Conclusions:

• Gait parameters can serve as objective biomarkers for assessing and predicting simulator sickness in VR.
• Optimized camera pose estimation in VR enhances user experience by mitigating simulator sickness and increasing presence.
• Future research should leverage gait analysis for developing more immersive and comfortable VR systems.