Eye-Tracking VR System for Nystagmus Treatment via Image Speed Synchronization
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Solution Overview
Problem
Individuals with nystagmus face challenges in clear vision due to involuntary eye movements, which existing treatments fail to effectively address, leading to potential developmental vision issues in children and shaky image perception in adults.
Innovation Solution
A system utilizing a VR headset with eye-tracking sensors and a console that synchronizes and adjusts the speed of images to retrain neural pathways, allowing users to control and slow down eye movements through incremental adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing treatments are used for nystagmus, then conventional therapy is provided, but the treatments fail to effectively address the involuntary eye movements and vision clarity issues
Solution Approach 1:
The system uses eye-tracking sensors to continuously monitor the user's eye movements and provides real-time feedback by adjusting the speed of displayed images to match the detected eye movement patterns. This closed-loop feedback mechanism enables the system to adapt to individual eye movement characteristics and progressively retrain neural pathways to reduce involuntary movements.
Solution Approach 2:
The system dynamically changes the speed parameter of displayed images based on detected eye movement characteristics. By adjusting image speed to match and then gradually diverge from eye movement patterns, the system induces neural adaptation that reduces the amplitude and velocity of involuntary eye movements over time.
2Manufacturing precision
If the speed of moving image is adjusted to retrain neural pathways, then vision clarity improves, but the system complexity increases due to eye-tracking sensors and synchronized image rendering
Solution Approach 1:
The VR headset serves multiple functions: it provides immersive visual content, tracks eye movements via integrated sensors, and delivers therapeutic image rendering with adjustable speed parameters. This multi-functionality consolidates what would otherwise require separate devices into a single integrated system, managing complexity while maintaining therapeutic effectiveness.
Solution Approach 2:
The system automatically detects eye movement patterns and autonomously adjusts image speed parameters without requiring manual intervention. The eye-tracking sensors and rendering engine work together to self-regulate the therapeutic process, reducing the need for complex external control mechanisms and simplifying user interaction.
3Stability of the object's composition
If the image speed is synchronized to eye movements, then the image appears stationary improving vision perception, but the eye movements remain involuntary and rapid
Solution Approach 1:
The system first establishes image-speed synchronization to create a stable visual reference point that appears stationary to the user. This preliminary stabilization creates a foundation for subsequent neural retraining, where the brain begins to associate the stable image with reduced eye movement requirements, gradually slowing involuntary movements over time.
Solution Approach 2:
The system dynamically transitions from complete speed synchronization (creating stationary appearance) to gradual speed divergence (inducing motion perception). This dynamic adjustment allows the system to maintain image stability initially, then progressively challenge the neural pathways to reduce eye movement speed while preserving visual clarity.
Data Source
AI summary
A system is disclosed in which an eye-tracking sensor signal is received and a moving image is generated to be rendered on one or more displays based on the eye-tracking sensor signal. Responsive to an input control signal from a user-operable control device or based on a determination that the user's gaze direction is tracking the moving image, the system adjusts the moving image.