Visual Field Assessment Using Overlapping Stimuli and Adaptive Sampling
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Solution Overview
Problem
Current methods for assessing visual fields, such as static perimetry, suffer from undersampling and spatial aliasing, which lead to distortions and missed information due to coarse sampling grids that cannot capture rapid changes in sensitivity across the visual field.
Innovation Solution
The method involves presenting large, smooth-sided stimuli that overlap in space, minimizing spatial aliasing by ensuring they do not represent spatial frequencies higher than the sampling grid can accurately represent, and using a polar representation to characterize visual field changes, with edge-preserving filters to enhance elongated features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a coarse sampling grid is used to assess visual fields, then the assessment procedure is simpler and faster, but spatial aliasing and undersampling occur leading to distortions and missed information
Solution Approach 1:
The visual field assessment is divided into multiple passes: a first pass with a coarse sampling grid for quick overview, and a second pass with a fine sampling grid for detailed measurement in regions showing rapid sensitivity changes. This segmentation allows the system to balance speed and precision by applying different sampling densities to different regions based on their complexity
Solution Approach 2:
The sampling grid density is made dynamic rather than static. The system automatically adjusts the sampling density based on the detected complexity of sensitivity changes in each region. Areas with rapid sensitivity variations receive finer sampling, while uniform areas use coarser sampling, optimizing both speed and accuracy adaptively
2Measurement precision
If a fine sampling grid is used to capture rapid changes in sensitivity, then measurement precision improves, but the assessment becomes more complex and time-consuming
Solution Approach 1:
Different sampling densities are applied to different local regions of the visual field based on their specific characteristics. Regions with rapid sensitivity changes (high complexity) receive fine sampling grids, while regions with uniform sensitivity (low complexity) receive coarse sampling grids. This local adaptation ensures high precision where needed without unnecessarily increasing overall complexity
3Measurement precision
If small test stimuli are used to assess local visual sensitivity, then the ability to detect localized sensitivity changes improves, but spatial aliasing increases due to the coarse sampling grid
Solution Approach 1:
The assessment is segmented into two stages: first using large stimuli with coarse sampling to map overall sensitivity patterns, then using small stimuli with fine sampling in regions identified as having rapid sensitivity changes. This prevents spatial aliasing by ensuring that small stimuli are only used where the fine sampling grid can adequately capture their spatial frequency content
Solution Approach 2:
A preliminary assessment using large stimuli and coarse sampling is performed before the detailed assessment with small stimuli. This preliminary pass identifies regions of interest where rapid sensitivity changes occur, allowing the system to concentrate fine sampling resources only where small stimuli are appropriate, thereby avoiding spatial aliasing in regions where it would occur
Data Source
AI summary
A method for assessing the function of at least one sensory field of a subject, and apparatus and systems for carrying out the method, the method comprising: using a display, presenting stimuli to selected locations of the sensory field, the selected locations being centered at points on a sampling grid spanning a portion of the sensory field, wherein the individual stimuli if presented simultaneously at the sampling grid points would overlap in the space defined by the sensory dimensions of the field; using a sensor, detecting responses in the subject's sensory field evoked by the stimuli; and processing the detected responses to relate them to the function of the subject's sensory field at the selected locations.