Visual Field Testing Using Segmented Interpolation
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Solution Overview
Problem
Existing visual field testing methods impose a burden on subjects and are inefficient in accurately measuring and estimating visual field sensitivities across the entire visual field, particularly in cases with visual field defects like glaucoma, where data interpolation can lead to erroneous results due to correlations between different areas.
Innovation Solution
A visual field testing method and device that divide the visual field into partial areas, measure sensitivities of initial test points, and estimate sensitivities of additional test points using a cumulative function and stochastic processes like Gaussian process regression, independently interpolating data in each area to minimize errors and reduce the number of necessary tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual field testing is performed across the entire visual field, then measurement completeness is improved, but test time and subject burden increase
Solution Approach 1:
The visual field testing area is divided into multiple regions (first partial area and second partial area). The system performs sensitivity measurements on a plurality of test points in the first partial area, then uses interpolation to estimate sensitivities in the second partial area. This segmentation allows complete visual field assessment without measuring every point directly, reducing test time while maintaining measurement completeness.
2Productivity
If data interpolation is performed across the entire visual field, then test efficiency is improved, but measurement accuracy deteriorates due to correlations between different areas
Solution Approach 1:
The visual field is divided into distinct partial areas (first and second partial areas). Interpolation is performed independently within each partial area rather than across the entire visual field. This prevents erroneous correlations between different visual field regions while maintaining test efficiency through selective interpolation in areas where it is most beneficial.
Solution Approach 2:
Different processing approaches are applied to different regions. The first partial area undergoes sensitivity measurement, while the second partial area uses interpolation based on measured data from the first area. This local differentiation optimizes both accuracy and efficiency for each specific region's characteristics.
3Measurement precision
If the number of test points is increased, then measurement accuracy is improved, but test burden on subject increases
Solution Approach 1:
The test points are divided into two groups: a plurality of first test points in the first partial area that are directly measured, and a plurality of second test points in the second partial area that are estimated through interpolation. This segmentation reduces the total number of direct measurements required from the subject while maintaining comprehensive visual field assessment accuracy.
Solution Approach 2:
Instead of directly measuring all test points, the system creates estimated sensitivity values for the second test points by interpolating from the measured first test points. This copying approach reduces subject burden while providing comprehensive visual field data.
Data Source
AI summary
A visual field testing method is a visual field testing method of testing a visual field range divided into at least a first partial area and a second partial area, the method including: a step of measuring sensitivities of a plural first test points that are included in the first partial area: and a step of performing a process of estimating sensitivities of a plural second test points that are included in the first partial area and are test points other than the first test points, by using the sensitivities of the plural first test points.