Eye Tracking Irlen Syndrome Diagnostic System
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Solution Overview
Problem
Individuals with Irlen Syndrome face reading difficulties due to overstimulation from certain visible wavelengths, which existing manual diagnostic and treatment methods struggle to accurately address, especially in dynamic environments and for children, leading to suboptimal filter selection and impaired reading capabilities.
Innovation Solution
A system that uses eye movement tracking and a pattern stability analyzer to automatically detect Irlen Syndrome and adjust the screen background color in real-time, utilizing a 32-bit color palette to provide user-specific solutions without requiring conscious user input, integrated into computing devices like laptops and mobile phones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual diagnostic methods are used to identify Irlen Syndrome, then the diagnostic process can be performed with simple equipment, but the accuracy and reliability of diagnosis deteriorates due to subjectivity and inconsistency
Solution Approach 1:
The patent replaces manual, subjective diagnostic methods with an automated computer-based system that uses eye tracking technology and algorithmic analysis. The system substitutes human observer judgment with objective computational analysis of eye movement patterns, thereby improving diagnostic precision while managing complexity through software automation.
Solution Approach 2:
The system enables automatic self-diagnosis and self-adjustment where the computing device autonomously monitors eye movements, analyzes patterns, identifies Irlen Syndrome presence, and adjusts display parameters without requiring manual intervention or external diagnostic equipment. This self-service approach improves accuracy while keeping the system integrated within the existing device.
2Ease of operation
If colored filters are used to compensate for Irlen Syndrome symptoms, then reading difficulty can be alleviated, but the selection of appropriate filters becomes complex and time-consuming
Solution Approach 1:
The system automatically performs filter selection by analyzing eye movement patterns and computing the optimal color filter parameters that will alleviate the user's symptoms. This eliminates the manual trial-and-error process where users or practitioners would otherwise need to test multiple filter combinations, significantly reducing both the time required and the operational complexity of filter selection.
Solution Approach 2:
The system uses real-time eye movement tracking as feedback to continuously monitor reading difficulty and automatically adjust filter parameters. The eye movement data provides objective feedback about the effectiveness of current filter settings, enabling automated optimization without requiring user input or manual adjustment, thus simplifying operation and reducing time loss.
3Measurement precision
If eye movement tracking is implemented to detect Irlen Syndrome, then diagnostic accuracy improves through objective measurement, but device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The patent leverages the existing camera and display components of standard computing devices to perform eye movement tracking and Irlen Syndrome diagnosis. By making the system multi-functional - using the camera for both general device functions and specific eye tracking, and the display for both content presentation and diagnostic stimulation - the patent improves measurement precision without significantly increasing overall device complexity, as existing components are repurposed rather than adding entirely new hardware subsystems.
Data Source
AI summary
An example system includes a camera and a display operable to display text to a human. The system is operable to perform a method that includes tracking, with the camera, eye movements of a human as the human reads text presented by the display, collecting eye movement data, analyzing the eye movement data, based on the analyzing, determining whether or not Irlen Syndrome is indicated by the eye movement data, and when Irlen Syndrome is indicated, adjusting a parameter of the display.