AI Eye Gaze Tracking for Quantitative Developmental Screening
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Solution Overview
Problem
Current diagnostic methods for developmental, cognitive, social, or mental disabilities, such as ADHD and autism spectrum disorders, are costly, time-consuming, and lack quantitativeness, often relying on subjective judgment, leading to inconsistent diagnoses and potential misdiagnoses, and are not easily accessible or suitable for children due to bulky equipment and complex calibration processes.
Innovation Solution
Employing artificial intelligence (AI) for real-time analysis of eye gaze and head pose using a tablet computer to pre-screen, detect, and monitor these disabilities, providing objective and quantitative measurements through eye gaze tracking, and integrating gamification elements to enhance user engagement and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual screenings and assessments are conducted by healthcare providers, then diagnostic capability is achieved, but the process becomes expensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical assessment processes with an automated computer-based system that captures images, detects facial landmarks, tracks eye gaze, and analyzes head pose automatically. This substitution eliminates the need for time-consuming manual screenings while maintaining diagnostic capability through objective quantitative measurements.
Solution Approach 2:
The system enables self-administered screening where individuals can complete the assessment independently using the computer-based interface. The automated image capture, analysis, and report generation allow the system to serve itself without requiring continuous healthcare provider involvement, significantly reducing time and cost.
2Measurement precision
If special equipment in laboratory is used for diagnosis, then diagnostic accuracy is improved, but accessibility deteriorates due to bulkiness and cost
Solution Approach 1:
The patent uses standard computer cameras and displays to create a portable copy of laboratory-grade diagnostic functionality. Instead of requiring bulky specialized equipment, the system replicates diagnostic capabilities using readily available consumer technology, making it accessible in ordinary settings while maintaining measurement precision through sophisticated image analysis algorithms.
Solution Approach 2:
The system is designed to be universally applicable across different settings using standard computer hardware. The same computer with camera and display can perform diagnostic assessments in clinics, schools, or home environments, eliminating the need for specialized laboratory equipment and improving accessibility without sacrificing diagnostic accuracy.
3Measurement precision
If complex calibration process is performed before diagnosis, then measurement accuracy is improved, but device complexity and user stress increase
Solution Approach 1:
The system performs automatic self-calibration by capturing images and automatically detecting facial landmarks, eye positions, and head pose parameters. The computer vision algorithms automatically adjust and optimize measurement parameters without requiring manual calibration procedures, eliminating complexity and user stress while maintaining measurement accuracy.
Solution Approach 2:
Manual calibration procedures are replaced with automated computer vision-based calibration. The system uses image processing and machine learning algorithms to automatically determine optimal measurement parameters, substituting complex mechanical calibration processes with intelligent software-based solutions that are both accurate and simple to execute.
4Productivity
If traditional diagnostic methods are used, then diagnostic process is completed, but quantitativeness and objectivity are lacking
Solution Approach 1:
The patent replaces subjective manual assessment with objective computer-based measurement. The system quantifies eye gaze patterns, head pose parameters, and facial landmark positions using precise image processing algorithms, transforming qualitative diagnostic observations into quantitative data that can be objectively analyzed and compared.
Solution Approach 2:
The system provides objective feedback through automated analysis of visual behavior data. By continuously measuring and analyzing eye gaze, head pose, and facial movements, the system generates quantitative metrics that provide clear, objective feedback on diagnostic parameters, eliminating subjective judgment and improving measurement precision.
Data Source
AI summary
Methods and apparatuses for pre-screening, detecting or monitoring developmental, cognitive, social, or mental disabilities or abilities. The simple, low-cost, quick and highly deployable methods and apparatuses employ artificial intelligence (AI) to analyze at least an individual's gaze pattern in response to a visual stimulus. The method comprises detecting a head and an eye region of the individual, obtaining a head pose of the individual, comparing the obtained head pose with a predetermined threshold range, obtaining one or more eye gaze parameters with regard to individual's eye gaze towards at least one point-of-interest in the visual stimulus using the selected eye gaze direction based on the head pose comparison step.