The Need:

Visual sensitivity testing plays a crucial role in assessing human vision and detecting potential visual impairments. However, traditional methods often lack the precision required to isolate specific frequency-specific channels in the visual system. There is a commercial need for a technology that can provide quick, accurate, and efficient contrast sensitivity function (CSF) estimation using computationally intense algorithms, allowing for a comprehensive assessment of visual sensitivity across various spatial and temporal frequencies. Addressing this need will enable better diagnosis and management of visual disorders and significantly improve the quality of visual assessments in various industries.

The Technology:

The presented technology utilizes adaptive testing methods and Bayesian adaptive inference to estimate spatial, temporal, and spatio-temporal contrast sensitivity functions (CSFs) in vision. By characterizing the results of visual sensitivity tests and utilizing statistical inference, the technology accurately determines visual sensitivity parameters across different contrasts and spatial frequencies. The iterative Bayesian inference employed in the technology ensures precise estimation by presenting visual stimuli, receiving responses, and iteratively determining subsequent stimuli based on Bayes rule and stopping conditions. The technology's flexibility allows it to be used with various visual stimuli, such as band-pass frequency letters, localized windowed gratings, and dynamic band-pass letter charts.

Commercial Applications:

• Visual Function Assessment: The technology can be employed in ophthalmology clinics and vision centers to assess visual function accurately. It aids in diagnosing visual impairments and tracking visual changes over time.
• Mobile Vision Testing: The first visual sensitivity test can be performed using a mobile device, making it accessible to a wider audience and enabling remote vision assessments.
• Vision Research: Researchers can utilize this technology to conduct in-depth studies on visual sensitivity across different visual field locations, illumination conditions, and external illumination noise levels.
• Industrial Vision Testing: The technology finds application in industries where precise visual assessment is critical, such as aviation, automotive, and manufacturing, ensuring optimal vision capabilities in workers.
• Vision Enhancement: By understanding visual sensitivity variations, the technology can contribute to the development of vision enhancement techniques and products for individuals with specific visual limitations.

Benefits/Advantages:

• Precision and Accuracy: The technology's adaptive testing methods and Bayesian inference ensure highly accurate and precise estimation of visual sensitivity parameters, surpassing traditional testing approaches.
• Efficiency and Speed: With quick CSF estimation, the technology reduces the time required for visual sensitivity testing, improving the efficiency of vision assessments in clinical and industrial settings.
• Customizable Stimuli: The technology allows the use of various visual stimuli, enabling tailored assessments based on specific requirements or conditions.
• Remote Accessibility: With the potential for mobile vision testing, the technology facilitates remote visual assessments, increasing accessibility for patients and researchers alike.
• Enhanced Vision Management: By providing comprehensive visual sensitivity information, the technology aids in better management of visual impairments and personalized vision enhancement strategies.

In conclusion, the presented technology meets the commercial need for accurate and efficient visual sensitivity testing by utilizing adaptive testing methods and Bayesian inference. With applications in various industries and research fields, it offers multiple benefits, such as precision, efficiency, and accessibility, making it a valuable asset in the realm of visual assessment and enhancement.