Peripheral Vision Training Using Visual Markers and Search Paths
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Solution Overview
Problem
Current technologies fail to effectively improve and maintain the quality of peripheral vision, as visual acuity decreases significantly from the central fovea to the periphery, limiting the ability to identify objects outside the central field of view.
Innovation Solution
A method and apparatus that utilize a processor and image sensor to define search paths within images, detecting transitions and adjusting parameters to enhance the identification of features and motion in peripheral regions, mimicking human eye movements to improve peripheral vision by training the subject to use peripheral vision for object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses a single search path for image processing, then the processing speed is maintained, but the detection precision of transitions in peripheral regions deteriorates
Solution Approach 1:
The patent divides the image processing into multiple search paths: a first search path for initial transition detection and a second search path for refined detection along the transition. This segmentation allows the system to maintain processing efficiency while improving detection precision by distributing the analysis across structured pathways.
Solution Approach 2:
The patent implements dynamic search path selection where the system adapts the search strategy based on detected transitions. When a transition is detected on the first search path, the system dynamically activates a second search path that follows the transition, creating a flexible, adaptive processing structure rather than a fixed complex system.
2Area of stationary object
If the system focuses on central vision processing, then the processing speed is maintained, but the field of view coverage deteriorates
Solution Approach 1:
The patent applies partial action by implementing a two-stage search approach where the first search path performs a broader, less intensive scan to detect transitions, and only regions with detected transitions proceed to the more intensive second search path. This allows extended field of view coverage without uniformly applying full processing intensity across the entire area, thus avoiding excessive processing time.
3Measurement precision
If the system increases visual acuity in peripheral regions, then the object identification capability improves, but the processing complexity increases
Solution Approach 1:
The patent implements local quality by applying different processing intensities to different regions of the image. The second search path is activated specifically along detected transitions in peripheral regions, providing enhanced local analysis where needed, while central regions and non-transition areas maintain standard processing. This localized enhancement improves peripheral acuity without uniformly increasing overall system complexity.
Data Source
AI summary
Systems and methods for improving the peripheral vision of a subject are disclosed. In one aspect, embodiments of the present disclosure includes a method, which may be embodied on a system, for improving peripheral vision of a subject using a visual marker on a display screen, the method includes, displaying a peripheral target on the display screen, the peripheral target having a visually discernable characteristic and determining whether the subject is able to correctly identify the peripheral target displayed on the display screen using the peripheral vision. The visual marker is intended for viewing using central vision of the subject and the peripheral target is intended for identification using the peripheral vision of the subject.