VR Motion Sickness Detection Using Sway Pattern Analysis
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Solution Overview
Problem
Existing technologies fail to effectively prevent motion sickness in virtual reality environments by identifying sensory conflicts before symptoms manifest, relying solely on post-sickness reactions.
Innovation Solution
A system that utilizes motion sensors and machine learning models to detect precursors of motion sickness through Fourier transforms and sway pattern analysis, providing advisories and adjusting display settings to mitigate risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion sensors and machine learning models are used to detect precursors of motion sickness, then motion sickness can be detected before symptoms manifest, but device complexity increases
Solution Approach 1:
The system performs preliminary detection of postural instability and sway patterns before motion sickness symptoms manifest. Motion sensors continuously monitor player posture and head movements, and machine learning models analyze these patterns to predict impending motion sickness, enabling preventive action before the harmful effect occurs.
Solution Approach 2:
The patent introduces motion sensors and machine learning models as intermediary components between the player's physical state and the VR system's response. These intermediaries detect subtle postural changes and translate them into actionable insights, bridging the gap between unconscious physiological responses and conscious system adjustments.
2Object-affected harmful factors
If display settings are adjusted to prevent motion sickness, then player comfort improves, but loss of information occurs as display quality is reduced
Solution Approach 1:
The system adjusts display settings in advance before motion sickness symptoms fully develop. By detecting early precursors such as increased sway amplitude or changed movement patterns, the system proactively modifies FOV, refresh rate, or other display parameters to prevent discomfort, rather than waiting for symptoms to manifest.
Solution Approach 2:
The patent implements dynamic adjustment of display settings based on real-time analysis of player motion data. The system continuously adapts display parameters such as field of view and refresh rate according to the player's current postural stability and motion patterns, optimizing the balance between comfort and visual quality throughout the gaming session.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early detection and prevention of motion sickness by altering display settings based on sensor data, reducing the likelihood of symptom onset.
Implementation Method 1
The motion sensor signals may be generated by at least one motion sensor on a head-mounted display (HMD) worn by the player
Implementation Method 2
More specifically, the method can include deriving at least one Fourier transform of the motion over time
Data Source
AI summary
Images 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.