Refractive Focus
Visual Assessment in the Digital Age
BY JASON MARSACK, PHD
One notable feature of digital tablet devices is the relatively intuitive nature of their operation. In other words, they are easy to use. Capitalizing on this, some visual assessment tasks relevant to eyecare clinics and vision science laboratories are becoming available as applications (apps) that run on tablets. The fact that developers can customize these apps allows for the streamlining of test execution and data management.
Many examples of the use of these devices in clinics and research laboratories can be found in the peer-reviewed literature. This article will not deliver an exhaustive list of all possible uses of this technology as it pertains to vision; rather, it will highlight several different examples of the deployment of tablet-based technology for use in clinical and/or laboratory settings.
The tools described here include tests to determine contrast sensitivity in a rapid manner, an app that facilitates a broad range of psychophysical tests, and an app that allows investigators to interact with and analyze research data. In each of these cases, the tools are running on a tablet device.
Quantifying a Patient’s Visual Performance
Quantifying visual performance is a hallmark of assessment in both clinic and laboratory settings. Contrast sensitivity is an important clinical measurement because it describes visual performance as a function of the spatial detail in the target as well as the relative luminance of different regions of the target.
Even though the information produced by the contrast sensitivity test is valuable, utilization in the clinical environment is relatively low (as compared to more ubiquitous tests such as high contrast visual acuity), which may be in part due to the time-consuming nature of the test. That said, methods have been developed to obtain contrast sensitivity information in a time-efficient manner on tablet devices. Two such methods are described here.
Kollbaum et al (2014) described the validation of the Ridgevue Contrast Sensitivity Test (Ridgevue Vision), a tablet-based letter contrast sensitivity test. The test is delivered as an iBook, which can be displayed on a tablet, and measures contrast sensitivity with letters of constant size subtending 2.8 x 2.2 degrees. During testing, a series of letter pairs are presented, and the contrast is continually decreased. Figure 1 depicts two letters from this test presented on a tablet screen.
Figure 1. Two letters from the Ridgevue letter contrast sensitivity test are presented on a tablet device.
Kollbaum et al (2014) found this test to produce repeatable results, which were also in agreement with the Freiburg Vision Test (FrACT; a free computer-based test found at www.michaelbach.de/fract/index.html). Its results were also slightly higher compared to values produced with the Pelli-Robson Contrast Sensitivity Chart (Precision Vision).
In another effort to measure contrast sensitivity, Dorr et al (2013) described results from proof-of-principle tests implemented on tablet devices. Their method of obtaining the contrast sensitivity function (CSF) is based on the quick CSF procedure reported by Lesmes et al (2010).
One of their reported tests utilized horizontally-oriented Gabor patterns and a two-alternative forced choice testing paradigm to assess contrast sensitivity at several spatial frequencies. These data were then used to reconstruct the CSF.
The experimenters found that the test can be conducted quickly and that the tablet-based implementation produced data that was in excellent agreement with test results obtained on more traditional computer-based laboratory equipment.
Psychophysical Testing
The examples above describe attempts to perform a specific psychophysical test: measurement of contrast sensitivity. However, myriad psychophysical tests could be performed in the laboratory environment. To this end, a generalized app that facilitates the execution of a wide variety of psychophysical tests would be advantageous.
Turpin et al (2014) described an application that they titled PsyPad (a wiki is available at psypad.net.au) that provides this generalized functionality. PsyPad allows the execution of user-defined tests without the need to perform the detailed programming that enables the test.
Instead, the experimenter first builds the visual stimuli to be used for the test in a separate environment; for example, stimuli can be constructed in Matlab or R. These stimuli are then transferred to the tablet and presented to the subject. Turpin et al also describe several examples of tests that can be executed with PsyPad, including questionnaires and assessment of visual stimuli.
Image Analysis
While the first three examples described apps that test the visual performance or preference of an individual patient/subject, there is also increasing interest in apps that allow an experimenter to interface with data that has previously been collected. One such example of this interface is in counting different cell types from images recorded during imaging experiments.
Templeton et al (2014) describe an app named ImagePad (CoDesign Engineering Services, LLC), which provides users with tools to count objects on an image displayed on the tablet screen using a manual counting method.
Among other uses, this app can be used to count the number of axons present in images of the optic nerve head. While not stated in their article, one could imagine applying this technique to images of other structures in the eye, such as corneal endothelial cells.
Global Constraints Associated with Digital Devices
While there is much excitement surrounding the utility and benefits of these devices in the laboratory and clinical environments, challenges inherent to their use do exist.
For instance, when presenting a visual stimulus, it is critical to carefully validate the characteristics of that stimulus. This is paramount when testing contrast sensitivity, in which calibration of grey levels and proper scaling of the stimulus are critical. Further complicating this task is the fact that the display characteristics across devices may vary (Kollbaum et al, 2014).
Also of concern when dealing with patient/subject data, and regardless of the intended utility of the app, patient/subject privacy protocols must always be followed.
Summary
Given the ubiquity of electronic devices in our daily lives, it is not surprising that they are finding utility in clinical and laboratory use. Their ease of operation and customizable nature almost ensures that an ever-growing number of applications for clinic and laboratory use will be delivered on tablet devices. CLS
To obtain references for this article, please visit http://www.clspectrum.com/references and click on document #237.
Disclosure: Dr. Mark Bullimore, developer of the letter contrast sensitivity test distributed by Ridgevue Publishing, is a collaborator on the laboratory-based research of Dr. Marsack.
Dr. Marsack completed a PhD in Physiological Optics and Vision Science at The University of Houston, College of Optometry, where he is currently a member of the faculty. He is affiliated with the Visual Optics Institute and The Ocular Surface Institute. His research interests include optical aberration of the eye, custom and pseudo-custom correction of optical aberration, visual performance, and optically based metrics predictive of visual performance.