Real-time motion sickness measurement: Feasibility and application of the real-time motion sickness scale (RMS)

Area of Science:

• Human-Computer Interaction
• Transportation Psychology
• Biomedical Engineering

Background:

• Motion sickness poses a significant barrier to user experience and adoption of new technologies like electric vehicles.
• Existing motion sickness questionnaires lack the temporal and symptom-specific detail required for accurate real-time data collection.
• Predictive models for motion sickness require precise measurements of variations across diverse environments.

Purpose of the Study:

• To introduce the Real-Time Motion Sickness Scale (RMS) for continuous monitoring of motion sickness symptoms.
• To address the limitations of current questionnaires in providing accurate, real-time motion sickness data.
• To improve the accuracy of motion sickness predictive models.

Main Methods:

• Developed the Real-Time Motion Sickness Scale (RMS) by enhancing existing questionnaires via systematic literature review and pilot testing.
• Validated the RMS feasibility through a real-driving experiment involving 24 passengers in an electric vehicle.
• Collected data on motion sickness severity and real-time changes during the experiment.

Main Results:

• The Real-Time Motion Sickness Scale (RMS) demonstrated feasibility and effectiveness in a real-world driving scenario.
• The RMS accurately quantifies motion sickness severity and captures dynamic changes over time.
• Data indicated the RMS's utility in understanding motion sickness in provocative environments.

Conclusions:

• The Real-Time Motion Sickness Scale (RMS) is a practical tool for real-time motion sickness assessment.
• RMS enables detailed monitoring of motion sickness, crucial for improving user experience with new technologies.
• The scale has significant applications in environments designed to provoke motion sickness.