Game Console Camera Motion Sickness Detection From Player Sway
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Solution Overview
Problem
Existing technologies fail to effectively prevent motion sickness in computer gamers by identifying sensory conflicts before symptoms manifest, relying solely on post-sickness reactions.
Innovation Solution
A system that uses camera images and machine learning models to detect precursors of motion sickness through Fourier transforms and sway patterns, providing advisories and adjusting display settings to mitigate risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensory conflict theory is used to investigate motion sickness after it occurs, then understanding of motion sickness mechanisms is improved, but ability to prevent motion sickness before symptoms manifest deteriorates
Solution Approach 1:
The system performs preliminary detection of postural instability and sway patterns before motion sickness symptoms manifest. By analyzing camera images to detect changes in postural stability and applying Fourier transforms to identify characteristic sway frequencies, the system issues warnings in advance, allowing preventive action before the harmful effect (motion sickness) occurs.
Solution Approach 2:
The system continuously monitors player postural stability through camera images and provides real-time feedback about motion sickness risk. The feedback loop includes detecting sway patterns, analyzing them through Fourier transforms, comparing against motion sickness thresholds, and issuing warnings or adjusting display settings accordingly, creating a closed-loop prevention system.
2Measurement precision
If camera images are processed to detect postural instability and sway patterns, then early detection of motion sickness is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The system extracts only the essential features from camera images needed for motion sickness detection - specifically postural stability metrics and sway patterns. Rather than processing entire images, the system identifies key regions (player position, orientation, movement patterns) and extracts relevant temporal frequency characteristics through Fourier transforms, reducing computational load while maintaining detection precision.
3Object-affected harmful factors
If display settings are adjusted automatically to prevent motion sickness, then player comfort is improved, but loss of display quality and immersion deteriorates
Solution Approach 1:
The system dynamically adjusts display settings based on real-time detection of postural instability and motion sickness risk. Rather than using fixed settings, the system modulates field of view, refresh rate, and other display parameters in response to detected sway patterns, optimizing both player comfort and display quality adaptively throughout the gaming session.
Data Source
AI summary
Images from a camera such as on a computer game console or other device of a player of a computer game are analyzed to determine whether motion of the player such as sway may resemble a precursor motion pattern to motion sickness, so that the player may be advised accordingly before the symptoms of motion sickness manifest themselves.