Lazy Eye Training via Dynamic Display Orientation
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Solution Overview
Problem
Current treatments for amblyopia, or lazy eye, require active compliance and often result in minimal effectiveness due to poor compliance and variable outcomes, especially when not initiated at an early age.
Innovation Solution
A computer-based system that determines a comfortability-tension threshold for the user, compares their current pose to an optimal pose, maps this to an angle for adjusting on-screen content, and adjusts the content accordingly to train the lazy eye without the need for extra sensors or devices, using an autoregressive neural network model to balance comfort and training effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If eye patching or atropine treatment is used to force usage of the lazy eye, then training effectiveness is improved, but user compliance deteriorates due to discomfort and inconvenience
Solution Approach 1:
The system automatically tracks user pose and adjusts content orientation without requiring manual intervention or special equipment from the user. The computer's existing camera and processing capabilities are utilized to self-monitor and self-adjust, eliminating the need for eye patches or medicated drops while maintaining training effectiveness.
Solution Approach 2:
The system dynamically changes the orientation parameter of on-screen content based on real-time detection of user head pose. By adjusting the content angle to match the user's natural viewing position, the system eliminates discomfort while ensuring the lazy eye is actively engaged, thereby maintaining compliance without sacrificing training effectiveness.
2Reliability
If traditional lazy eye training methods are implemented, then some training effect is achieved, but additional sensors and devices are required increasing system complexity
Solution Approach 1:
The system uses the computer's existing camera and display for dual purposes: normal computing tasks and lazy eye training. The camera serves both as a standard input device and as a pose-tracking sensor, while the display serves both as a normal output device and as the training medium. This eliminates the need for dedicated sensors and devices while maintaining training effectiveness.
Solution Approach 2:
The system leverages the computer's own existing hardware components (camera, display, processor) to perform the training function. No external sensors or specialized devices are needed because the computer already possesses the necessary capabilities for pose detection and content delivery, thereby reducing system complexity while achieving training goals.
3Reliability
If on-screen content is adjusted to train the lazy eye, then training effectiveness is improved, but user comfort may deteriorate if pose alignment is not optimized
Solution Approach 1:
The system continuously monitors user head pose through the camera and uses this feedback to dynamically adjust content orientation. This closed-loop control ensures that the content is always presented at the optimal angle for both training effectiveness and user comfort, preventing discomfort while maintaining the training effect.
Solution Approach 2:
The content orientation is not fixed but dynamically adjusted in real-time based on user pose changes. As the user moves their head, the system automatically recalculates and reorients the content to maintain proper alignment, thereby preserving both training effectiveness and user comfort throughout the training session.
Data Source
AI summary
A comfortability-tension threshold for a user is determined and a current pose of the user and a determined optimal pose are compared. The current pose and the determined optimal pose are mapped to an angle for adjusting on-screen content of a display of the computer system and the on-screen content of the display of the computer system is adjusted based on the angle.