Relative Eye Axial Length Analysis for Accurate Myopia Progression
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Solution Overview
Problem
Existing methods for checking myopia progression are inadequate as they rely solely on eye axial length, which is influenced by individual growth and body size, making accurate assessment of axial myopia progression difficult.
Innovation Solution
A system and method that calculates a relative eye axial length by relativizing the eye axial length using reference values such as pupillary distance, corneal curvature, or body dimensions, and compares it with population data to determine the relative position of the eye axial length, thereby excluding the influence of individual growth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the absolute value of eye axial length is used to check myopia progression, then the measurement is simple, but the accuracy is insufficient due to individual growth variations
Solution Approach 1:
The patent transforms the absolute eye axial length measurement into a relative measurement by introducing reference values (such as head circumference or body height) to create a normalized index. This parameter transformation allows the system to maintain measurement simplicity while eliminating the influence of individual growth differences, thereby resolving the contradiction between ease of operation and measurement precision.
2Measurement precision
If reference values such as head circumference or body height are introduced to normalize eye axial length, then the accuracy of myopia progression check is improved, but the device complexity increases
Solution Approach 1:
The patent employs reference values such as head circumference or body height that can be measured using standard anthropometric methods already available in clinical settings. These multi-functional parameters serve both as growth indicators and as normalization factors for eye axial length, allowing the system to improve measurement precision without significantly increasing device complexity.
3Reliability
If population information is used for comparison, then the reliability of myopia diagnosis is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent replaces complex manual comparison processes with automated computational algorithms that calculate relative eye axial length indices and compare them against population databases. This substitution of mechanical/data processing methods with computational systems maintains high diagnostic reliability while reducing the practical difficulty of detection and measurement.
Data Source
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AI summary
Disclosed is a myopia progression analysis device including: an eye axial length acquisition section 111 that acquires an eye axial length of an eye of a subject; a reference value acquisition section 112 that acquires a numerical value related to a physical characteristic of the subject other than the eye axial length as a reference value; a relative eye axial length calculator 113 that calculates a relative eye axial length through relativization of the eye axial length acquired by the eye axial length acquisition section 111 using the reference value acquired by the reference value acquisition section 112; a population information acquisition section 114 that acquires population information which is a set of information about relative eye axial lengths of a plurality of comparison targets to be compared with the subject; and a relative position information calculator 115 that compares the relative eye axial length of the subject calculated by the relative eye axial length calculator with the relative eye axial lengths of the plurality of comparison targets included in the population information to calculate relative position information indicating a relative position of the relative eye axial length of the subject in the set of comparison targets.