Adaptive Vision Testing via Prediction-Based Stimuli Selection
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Solution Overview
Problem
Current vision defect determination methods are slow and inefficient, requiring users to maintain a fixed head position for extended periods, which can be uncomfortable and impractical for all ages, and often necessitate expensive specialized equipment.
Innovation Solution
The use of a head-mounted display or wearable device that dynamically determines stimuli characteristics for vision defect determination during a vision test, reducing the time needed for users to maintain a fixed head position without compromising testing effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional vision testing methods are used, then comprehensive vision defect determination can be achieved, but the testing process becomes slow and inefficient requiring extended fixed head position
Solution Approach 1:
The patent applies dynamics by transitioning from static, predetermined stimulus sequences to dynamic, adaptive stimulus selection. The system dynamically adjusts stimulus characteristics (location, type, intensity) based on real-time user responses and predictions, allowing the testing process to adapt to individual user needs and reduce unnecessary testing time while maintaining comprehensive defect detection.
Solution Approach 2:
The patent utilizes parameter changes by modifying stimulus characteristics dynamically during the testing process. Instead of following a fixed sequence, the system changes parameters such as stimulus location, contrast, and type based on predicted visual field defects and user responses, optimizing the testing efficiency and reducing the time required for comprehensive vision assessment.
2Measurement precision
If users maintain fixed head position for extended periods, then accurate vision testing can be performed, but user comfort deteriorates and the process becomes impractical for some users
Solution Approach 1:
The system dynamically adapts the testing protocol based on user responses and predicted defects, allowing for more flexible testing that reduces the need for extended fixed head positions. This dynamic approach maintains testing accuracy while improving user comfort by avoiding unnecessary prolonged fixation requirements.
3Ease of operation
If specialized equipment with headrests and supports is used, then user comfort during extended testing is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical support systems (headrests, physical supports) with a software-based adaptive testing protocol. By using prediction models and dynamic stimulus selection, the system eliminates the need for specialized physical equipment while maintaining user comfort and testing effectiveness through intelligent control rather than mechanical constraints.
4Measurement precision
If conventional vision testing protocols are used, then comprehensive testing can be conducted, but the testing process becomes inefficient and requires many combinations of locations and characteristics
Solution Approach 1:
The system performs preliminary actions by using prediction models to anticipate likely visual field defects before conducting comprehensive testing. This allows the system to prioritize testing locations and stimulus characteristics that are most likely to reveal defects, reducing the total number of combinations needed while maintaining detection completeness.
Solution Approach 2:
The patent implements feedback mechanisms where user responses to stimuli are continuously monitored and fed back into the prediction model. This feedback loop allows the system to adjust subsequent stimulus selection based on actual user performance, eliminating redundant testing combinations and improving overall testing efficiency while maintaining comprehensive defect detection.
Data Source
AI summary
In some embodiments, initial feedback indicating threshold characteristics (under which a user sees initial stimuli presented on a user interface) may be provided to a prediction model, and a set of predicted characteristics (for a set of locations of the user interface) may be obtained via the prediction model. Based on predicted characteristics associated with one or more selected locations, stimuli may be presented at the selected locations during the visual test presentation. Visual defect information for the user may be generated based on feedback from the visual test presentation. In some embodiments, the selection of the locations to be tested during a visual test presentation may be performed based on a set of confidence scores associated with the predicted characteristics. As an example, the locations may be selected over one or more other locations of the set of locations based on the set of confidence scores.