Automated Vision Assessment Using Gaze Tracking
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Solution Overview
Problem
Current vision assessment methods require manual responses and verbal communication, are subjective, and demand trained personnel, making them inefficient and challenging for elderly subjects, especially when dealing with varying vision conditions and potential lack of fixation due to fatigue.
Innovation Solution
An automated system that determines personalized test patterns based on preliminary eye assessments, collects gaze data without requiring central fixation, and assesses vision functionality using an eye tracker, reducing manual effort and enabling operation by trained nurses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual responses and verbal communication are required for vision assessment, then the assessment can be conducted with simple equipment, but the subject fatigue increases and the reliability decreases
Solution Approach 1:
The system automatically tracks and records the subject's gaze movements without requiring manual responses or verbal communication. The eye tracker captures fixation points and saccades autonomously, eliminating the need for subject participation beyond natural viewing behavior.
Solution Approach 2:
The patent replaces manual response mechanisms with automated eye tracking technology. Instead of requiring subjects to press buttons or speak, the system uses optical sensors to detect and record gaze patterns, substituting mechanical and physiological response systems with optical detection.
2Measurement precision
If trained personnel such as doctors or ophthalmologists are required to conduct the tests, then the assessment accuracy is improved, but the device complexity and cost increase
Solution Approach 1:
The system performs automated assessment by tracking gaze patterns and automatically interpreting results against normative data. The algorithm processes eye movement data to detect conditions like macular degeneration without requiring human interpretation, making the system self-sufficient for clinical assessment.
Solution Approach 2:
The system incorporates automated feedback mechanisms where gaze data is continuously analyzed and compared against established criteria. The algorithm provides real-time assessment feedback, eliminating the need for trained personnel to interpret results manually.
3Reliability
If central fixation is required throughout the test, then the test procedure is simplified, but the reliability decreases due to fatigue and inability to maintain fixation
Solution Approach 1:
The system performs preliminary calibration to establish the subject's natural fixation behavior before the actual assessment. This preliminary phase captures baseline gaze patterns, allowing the system to adapt to individual variations in fixation ability without requiring perfect fixation during testing.
Solution Approach 2:
The system dynamically adapts to the subject's gaze behavior rather than requiring static fixation. The eye tracker continuously adjusts to capture natural eye movements, allowing the assessment to proceed even when subjects cannot maintain fixed gaze due to fatigue or visual impairment.
4Measurement precision
If standardized test procedures are applied to all subjects, then the testing process is streamlined, but the measurement precision decreases for subjects with varying vision conditions
Solution Approach 1:
The system dynamically adapts the test parameters based on real-time gaze data and subject response patterns. The algorithm adjusts stimulus presentation and analysis criteria to match individual vision conditions, providing personalized assessment without requiring separate standardized protocols for each condition.
Solution Approach 2:
The system automatically modifies test parameters such as stimulus duration, intensity, and positioning based on detected gaze patterns and vision condition indicators. This parameter adaptation occurs seamlessly during testing, maintaining precision across diverse subjects without extending test duration.
Data Source
AI summary
The present disclosure generally relates to automated method and system for vision assessment of a subject. The method comprises: determining a set of test patterns for the subject based on a preliminary assessment of an eye of the subject; displaying the set of test patterns sequentially to the subject; collecting data on the subject's gaze in response to each test pattern displayed to the subject; and assessing vision functionality of the subject based on the collected gaze data.