Automated Vision Test

optics
Automated Vision Test (TOP2-146)
Patent Only, No Software Available For License.
Overview
Visual acuity (clearness of vision), usually measured by an eye doctor using an eyechart, is one of the most commonly applied clinical tests in the world. With the patients participation, it measures the smallest letters that can be reliably identified at a specified distance, and thereby tests the resolving power of our eyes. The result, often quoted as a pair of numbers like 20:20, lets us know if corrective lenses or refractive surgery can help us better perform tasks like reading or driving. This invention provides an automated system to estimate visual acuity based on objective measurements of the eye optics and wavefront aberrations (WA). WA are represented in a particular form known as the Zernike polynomials. The WFAMetric is an algorithm that converts the list of numbers into an estimate of the visual acuity of the patient. If changes are planned to the WA of the patient the predicted change in acuity can be calculated.

The Technology
The Wavefront Aberrations (WA) are a collection of different sorts of optical defects, including the familiar defocus and astigmatism that are corrected by eyeglasses, but also more complex higher order aberrations such as coma, spherical aberration, and others. The WA provide a comprehensive description of the optics of the eye, and thus determine the acuity. But until recently, a practical method of computing this relationship did not exist. Our solution to this problem is to simulate the observer performing the acuity task with an eye possessing a particular set of WA. When a letter is presented, we first distort a digital image of the letter by the specified WA, and add noise to mimic the noisiness of the visual system. From previous research, we have determined the appropriate noise level to match human performance. We then attempt to match the blurred noisy image to similarly blurred candidate letter images, and select the closest match. We repeat this for many trials at many letter sizes, and thereby determine the smallest letter than can be reliably identified: the visual acuity. We have streamlined and simplified the key steps for this simulation approach so that the entire process is robust, accurate, simple and fast. Results are typically obtained in a few seconds.
Automated Vision Test The technology could be used to expedite a patients vision testing.
Benefits
  • Connects wavefront aberrations to visual acuity
  • Operates accurately, simply, and fast
  • Incorporates optical and neural filtering, neural noise, and an ideal decision rule
  • Includes the actual optotypes and simulates the process of optotype recognition

Applications
  • Automated vision testing
  • Automatic prescriptions for eyeglasses and contact lenses
  • Custom optical implants, such as intraocular lenses
  • Prediction of acuity following laser surgery
  • Refinement of laser eye surgery methods
  • Ophthalmic aberrometers
Technology Details

optics
TOP2-146
ARC-16331-1
8,408,707
Predicting visual acuity from wavefront aberrations, 2008, Journal of Vision 8(4):17, 119
Similar Results
Video Acuity Measurement System
Video Acuity Measurement System
The Video Acuity metric is designed to provide a unique and meaningful measurement of the quality of a video system. The automated system for measuring video acuity is based on a model of human letter recognition. The Video Acuity measurement system is comprised of a camera and associated optics and sensor, processing elements including digital compression, transmission over an electronic network, and an electronic display for viewing of the display by a human viewer. The quality of a video system impacts the ability of the human viewer to perform public safety tasks, such as reading of automobile license plates, recognition of faces, and recognition of handheld weapons. The Video Acuity metric can accurately measure the effects of sampling, blur, noise, quantization, compression, geometric distortion, and other effects. This is because it does not rely on any particular theoretical model of imaging, but simply measures the performance in a task that incorporates essential aspects of human use of video, notably recognition of patterns and objects. Because the metric is structurally identical to human visual acuity, the numbers that it yields have immediate and concrete meaning. Furthermore, they can be related to the human visual acuity needed to do the task. The Video Acuity measurement system uses different sets of optotypes and uses automated letter recognition to simulate the human observer.
ARC RIG
Reconfigurable Image Generator and Database Generation System
The system, the Reconfigurable Image Generator (RIG), consists of software and a hardware configuration, and a Synthetic Environment Database Generation System (RIG-DBGS). This innovative Image Generator (IG) uses Commercial-Off-The-Shelf (COTS) technologies and is capable of supporting virtually any display system. The DBGS software leverages high-fidelity real-world data, including aerial imagery, elevation datasets, and vector data. Through a combination of COTS tools and in-house created applications, the semi-automated system can process large amounts of data in days rather than weeks or months, a disadvantage of manual database generation. A major benefit of the RIG technology is that existing simulation users can leverage their investment in existing real-time 3D databases (such as OpenFlight) as part of the RIG system.
Technology Example
Computational Visual Servo
The innovation improves upon the performance of passive automatic enhancement of digital images. Specifically, the image enhancement process is improved in terms of resulting contrast, lightness, and sharpness over the prior art of automatic processing methods. The innovation brings the technique of active measurement and control to bear upon the basic problem of enhancing the digital image by defining absolute measures of visual contrast, lightness, and sharpness. This is accomplished by automatically applying the type and degree of enhancement needed based on automated image analysis. The foundation of the processing scheme is the flow of digital images through a feedback loop whose stages include visual measurement computation and servo-controlled enhancement effect. The cycle is repeated until the servo achieves acceptable scores for the visual measures or reaches a decision that it has enhanced as much as is possible or advantageous. The servo-control will bypass images that it determines need no enhancement. The system determines experimentally how much absolute degrees of sharpening can be applied before encountering detrimental sharpening artifacts. The latter decisions are stop decisions that are controlled by further contrast or light enhancement, producing unacceptable levels of saturation, signal clipping, and sharpness. The invention was developed to provide completely new capabilities for exceeding pilot visual performance by clarifying turbid, low-light level, and extremely hazy images automatically for pilot view on heads-up or heads-down display during critical flight maneuvers.
A NASA researcher using the technology
Oculometric Testing for Detecting/Characterizing Mild Neural Impairment
To assess various aspects of dynamic visual and visuomotor function including peripheral attention, spatial localization, perceptual motion processing, and oculomotor responsiveness, NASA developed a simple five-minute clinically relevant test that measures and computes more than a dozen largely independent eye-movement-based (oculometric) measures of human neural performance. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance and may prove to be a useful assessment tool for mild functional neural impairments across a wide range of etiologies and brain regions. The technology may be useful to clinicians to localize affected brain regions following trauma, degenerative disease, or aging, to characterize and quantify clinical deficits, to monitor recovery of function after injury, and to detect operationally-relevant altered or impaired visual performance at subclinical levels. This novel system can be used as a sensitive screening tool by comparing the oculometric measures of an individual to a normal baseline population, or from the same individual before and after exposure to a potentially harmful event (e.g., a boxing match, football game, combat tour, extended work schedule with sleep disruption, blast or toxic exposure, space mission), or on an ongoing basis to monitor performance for recovery to baseline. The technology provides set of largely independent metrics of visual and visuomotor function that are sensitive and reliable within and across observers, yielding a signature multidimensional impairment vector that can be used to characterize the nature of a mild deficit, not just simply detect it. Initial results from peer-reviewed studies of Traumatic Brain Injury, sleep deprivation with and without caffeine, and low-dose alcohol consumption have shown that this NASA technology can be used to assess subtle deficits in brain function before overt clinical symptoms become obvious, as well as the efficacy of countermeasures.
Spatial Standard Observer (SSO)
Spatial Standard Observer (SSO)
The Spatial Standard Observer (SSO) provides a tool that allows measurement of the visibility of an element, or visual discriminability of two elements. The device may be used whenever it is necessary to measure or specify visibility or visual intensity. The SSO is based on a model of human vision, and has been calibrated by an extensive set of human test data. The SSO operates on a digital image or a pair of digital images. It computes a numerical measure of the perceptual strength of the single image, or of the visible difference between the two images. The visibility measurements are provided in units of Just Noticeable Differences (JND), a standard measure of perceptual intensity. A target that is just visible has a measure of 1 JND. The SSO will be useful in a wide variety of applications, most notably in the inspection of displays during the manufacturing process. It is also useful in for evaluating vision from unpiloted aerial vehicles (UAV) predicting visibility of UAVs from other aircraft, from the control tower of aircraft on runways, measuring visibility of damage to aircraft and to the shuttle orbiter, evaluation of legibility of text, icons or symbols in a graphical user interface, specification of camera and display resolution, inspection of displays during the manufacturing process, estimation of the quality of compressed digital video, and predicting outcomes of corrective laser eye surgery.
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