Probably best to do this VFT (visual field testing) app review from perspective of someone looking to set up a home VFT system (or, in my case, replace an existing one no longer being distributed). This will highlight what I’ve found important/useful, but is unlikely to match the reader’s needs and preferences exactly.
- app should be simple to use, reliable, store complete test results, etc. [In a search I did last year, MRF = Melbourne Rapid Fields looked like one of the better choices, from
https://glance-optical.com/, although when I last checked it required an iPad to run it, with there being a free Melbourne Rapid Fields version downloadable from App Store for US customers. In general, the US eye profession and FDA seems to be discouraging development and use of such at-home apps, which is a shame.]
- app should display stimuli (light dots) of varying size/intensity in a random manner over an area large enough to cover the retinal surface of interest (and I don’t want an app that gets too clever about what stimuli it bothers to display – just give me a fixed number of stimuli each time so I can count them)
- in the past, I’ve been testing 24 degrees, covered by 54 locations, 4 stimuli each location (like Humphrey’s 24-2 standard testing), so it would make the transition to a new app simpler if it supported a similar approach
- it would be nice to be able to test a wider area, or narrower area more densely, if desired, but not a deal breaker since the 24 degrees adequately covers my glaucomatous vision loss (and the corresponding number of locations and stimuli take a few minutes to cover, which is probably the limit on one’s attention span per test, especially if you want to do the tests fairly often)
- I’m not at all concerned that the app numerically match standard results (or even generate similar types of numbers), since that is likely a fool’s errand given the complexities involved, and will just distract you from focusing on what you need to do to reliably monitor your personal visual field response
- the app should (at least) report the total number of positives (clicks when stimulus was present), as well as false positives (clicks when stimulus not present, a measure of trigger-happiness) [I would then compare the positives reported to the count I did in my head of stimuli seen, choosing the lower of the two counts as the best estimate of the positive count for that test because (1) when my count < positives, then positives contain cases where stimulus was shown but I didn’t actually see it, and (2) less commonly, when my count > positives, then I must have seen stimuli that were not there (i.e., just noise in visual field)]
- results by location should be displayed in a grid similar to the standard output so that one can quickly see the variation in visual field sensitivity by retinal location, although this is not as reliable as the total positives count, since the grid location results are more subject to small variations in head location [OCT RNFL measurements are a more precise way of monitoring glaucomatous damage location]
- the app will inevitably attempt to cleverly do and calculate more stuff, which I’ll likely ignore [and if I can’t find an app that meets the above (simple) requirements, then I’ll probably just create one :)]
- follow the app’s instructions for head positioning (typically using blind spot location), plus any lighting or computer display tips
- choose a testing location where you can control ambient light, computer brightness, etc. [I do this in an office with shades closed, and a desk lamp on each side of the screen, which just happens to be my original setup from 10 years ago (i.e., probably not the best setup)]
- if testing both eyes, switch which eye is first tested each time to eliminate bias related to first vs. second testing (such as due to differences in fatigue, attentiveness, etc.); also avoid doing too many tests at one sitting, since this will introduce eye fatigue with lower visual field response
- limit distractions, and develop a routine that keeps you focused during testing; the simple counting I do of stimuli seen helps a lot, and gives you a sense of how far the test has progressed; if asked to focus on one location during the testing, try shifting focus slightly left or right after each stimulus to keep your eye from wandering (i.e., give it something to do -- some apps deal with this by having you move fixation from stimulus to stimulus, keeping the eye busy)
- choose testing times when you’re not emotional, tired, hungry, etc. [the exception to these tips being, of course, when you’re actually testing the effect of something you would normally control]
- block the non-tested eye in a way that is not stressful (use an eye occluder of some sort)
- develop a testing routine that maximizes test result (positive count) reproducibility/precision; on a positive count basis, it should be possible to routinely reproduce test results within a few counts of one another (out of 200+ stimuli), with a block of about 6 tests producing a well-distributed set of results about the mean
- if a set of associated test results are not well-disributed about their mean, then do more testing; don’t eliminate apparent outliers without doing sufficient retesting, and without a plausible reason for the outlier
- the reproducibility of your test results indicates what degree of visual field change is possible for you to determine with such testing [as illustrated by my comparison of B3 effects on VFCs, where significance required a difference in means beyond the imprecision of each block of tests – you can do a T-test, etc., to make it more complicated, but it should be obvious when plotted that result sets differ, or not]
- if making a significant change to your testing routine, do enough testing immediately before and after the change to measure the effect the change had on results
This approach will give you a good measure of your overall visual field response in each eye. And although the results will not be directly (numerically) comparable to others, or to results from standard testing, they need not be any less reliable, benefiting from the control of many factors ignored in standard testing, as well as the ability to do more testing as needed to overcome imprecision (averaging out sources of noise). Allowing you to answer lots of interesting questions about how lifestyle changes affect your vision.