Refractive Error Measurement Using Maximum Distance of Best Acuity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current optometric examination methods for refractive error measurement require professional intervention and reliance on subjective patient responses or less accurate objective methods, lacking efficiency and accuracy in self-administered assessments.
Innovation Solution
A system utilizing a personal device with a display and sensor, allowing users to conduct self-examinations by measuring the distance to a target image, calculating refractive error based on maximum distance of best acuity, and estimating dioptric power without the need for corrective lenses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective refraction method is used with professional examiner and trial lenses, then measurement accuracy is improved, but device complexity and professional intervention requirement increase
Solution Approach 1:
The system enables patients to perform self-refraction examinations using their personal computing devices. The application guides patients through the examination process, automatically presenting targets at calculated distances and interpreting responses to determine refractive error, eliminating the need for professional examiners and complex trial lens equipment.
Solution Approach 2:
The patent replaces the mechanical trial lens system with a computational approach. Instead of physically interposing lenses of various dioptric powers, the system uses software to present targets at dynamically calculated distances based on the patient's suspected refractive error, achieving the same diagnostic purpose through digital means.
2Ease of operation
If objective refraction methods such as auto refraction are used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The system incorporates iterative feedback mechanisms where the application adjusts target distance based on patient responses. The algorithm refines the estimated refractive error with each response, presenting subsequent targets at optimized distances, thereby improving measurement accuracy while maintaining ease of self-administration.
Solution Approach 2:
The examination process is dynamic rather than static. The system continuously adapts the target distance and presentation parameters based on real-time patient responses and the evolving estimate of refractive error, optimizing the measurement process throughout the examination.
3Measurement precision
If traditional subjective refraction with cross cylinder and trial frame is used, then measurement precision is improved, but ease of operation and productivity worsen due to professional intervention requirement
Solution Approach 1:
The system automates the entire refraction process including cylindrical power and axis determination. Patients independently complete the examination by responding to systematically presented targets, with the algorithm automatically calculating refractive parameters, eliminating the time-consuming manual process of professional examiners using cross cylinders and trial frames.
Solution Approach 2:
The system performs preliminary calculations of target distance and presentation parameters before each target is shown to the patient. This pre-computation optimizes the examination flow and enables rapid processing of multiple targets, increasing productivity while maintaining measurement precision.
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
Method and system for measuring refractive error of an eye of a subject, The method include: (a) displaying at least one dynamic target image of at least one sign over a display area; (b) receiving subjective feedback from the subject indicating that the subject is positioned at a maximum distance of best acuity (MDBA) from the target image, wherein the MDBA is the maximum distance in which the subject recognizes the sign; (c) measuring one or more parameter associated with distance, during the time the subject has reached the MDBA distance, using at least one sensor; (d) estimating the MDBA by estimating the distance between the eye of the subject and the display area in which the target image is displayed by using the sensor data and (e) calculating the refractive error of the eye according to the estimated MDBA and characteristics of the target image.