Ophthalmic Field-of-View Simulation Using Distance-Aware AR Rendering
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Solution Overview
Problem
Existing representations of ophthalmic conditions are difficult to adapt to individual user's experiences, and there is a need for accurate simulations of these conditions that are tailored to the user's environment and specific type and severity, especially when applying AR and VR technologies.
Innovation Solution
A computer-implemented system using a head-mounted display and computing device to receive user input, sensor data, and video, applying algorithms to simulate ophthalmic conditions in real-time, adjusting image alterations based on object distances and parameters such as age and severity, and providing realistic simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing representations of ophthalmic conditions are used, then the basic simulation function is provided, but the accuracy and adaptability to individual user experiences deteriorates
Solution Approach 1:
The system dynamically adjusts simulation parameters based on real-time sensor data capturing user eye movements, head position, and environmental context. The simulation adapts its characteristics to match individual user experiences and environmental conditions, transforming static representations into dynamic, personalized simulations that respond to user-specific factors.
Solution Approach 2:
The system modifies multiple simulation parameters including blur radius, contrast adjustment, color filtration, and field of view characteristics based on detected ophthalmic condition parameters. By changing these visual parameters in real-time according to user-specific condition data, the system achieves both high accuracy in representing the condition and adaptability to individual experiences.
2Adaptability or versatility
If generic ophthalmic condition simulations are applied, then the basic simulation function is provided, but the tailoring to specific type and severity deteriorates
Solution Approach 1:
The system segments the simulation process into distinct modules: sensor data acquisition, object detection and distance measurement, condition-specific algorithm application, and visual rendering. Each module handles specific aspects of the simulation, allowing complex tailoring to specific condition types and severities through modular composition rather than monolithic complexity.
Solution Approach 2:
The system applies different simulation algorithms and parameter settings to different regions and objects in the visual field based on their distance from the user and their relevance to the specific ophthalmic condition. This localized approach enables tailored simulations for specific condition types and severities without requiring complete system complexity throughout all areas.
3Measurement precision
If distance-based image alteration algorithms are applied, then the accuracy of ophthalmic condition simulation improves, but the processing time and computational load increases
Solution Approach 1:
The system performs preliminary object detection, classification, and distance estimation using sensor data and machine learning models before applying the full ophthalmic condition simulation algorithms. This preliminary processing identifies which objects require simulation and pre-calculates relevant parameters, reducing the computational time needed for the actual simulation while maintaining high accuracy.
Solution Approach 2:
The system applies simulation algorithms selectively to only those objects and regions that are most relevant to the detected ophthalmic condition and user context, rather than processing the entire visual field uniformly. This partial application approach maintains simulation accuracy for critical areas while reducing overall processing time and computational load.
Data Source
AI summary
Provided herein are methods and computer-implemented systems for simulating a field of view affected by an ophthalmological condition. The ophthalmological condition may be presbyopia. The method may comprise receiving from a user interface one or more parameters relating to said ophthalmic condition. The method may comprise receiving, from a head mounted display, sensor data and a video stream. The method may comprise using one or more computer processors, applying an algorithm to modify at least a portion of said video stream to generate a simulated field of view, wherein said modification is based at least in part on said sensor data, said video stream, and said one or more parameters. The method may comprise providing said simulated field of view affected by an ophthalmic condition to a user via a graphical interface. The sensor data may include location data of one or more objects within the field of view. The algorithm may be applied to the object based on its location from the head mounted display.