The AVTS (Advanced Vision Testing System)

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The AVTS system was developed in cooperation with a major Pharmaceutical company in order to test an individual's visual function more accurately.

Standard tests of vision (the regular eye chart) do not fully evaluate vision and do not accurately replicate vision in the real world. The standard eye chart contains letters that are black on white (100% Contrast) and can be viewed by the subject for an unlimited period of time before an answer is given.

Unfortunately, vision in the real world, and especially in Sports, is not like that!

In the real world, we must view targets that are faint, and often difficult to see against the background. In addition, we must recognize what we are seeing quickly and make a response immediately.  The standard eye charts simply do not provide the ability to test this level of vision and have been shown to be unrelated to sports performance.

In its place, we developed the AVTS system to test athletes. With this computer based system, we provide targets that are small, faint and only displayed for a short time. The subject must recognize the direction of a letter "C" target and provide an answer of the ring of the "C" being open to the right, left, upwards or downwards (see photo above). The test can be set at any level of difficulty, and it has been calibrated both for the general population as well as for the elite sports athlete.

Wheras the results of a standard vision do not correlate to actual on-field sports performance, the results of this test do correlate to on-field performance and can be used to both guide correction of vision as well as to determine potential success in sports. 

Several scientific papers have been published supporting this testing system and its results and three US Patents have been granted as well as many international patents based on the testing system design.

Additionally, during the COVID-19 pandemic, we created an online version of the test using artificial intelligence as well as specifically designed machine learning protocols to allow remote testing of athletes without the need for specific hardware. This test is browser based and can be completed with a single computer/laptop system.