Subjective Refraction Test Using a Smartphone for Vision Screening

Summary

This paper presents the protocols and clinical validation data for using a smartphone app to subjectively measure refractive error.

Abstract

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing any external attachment, the app running on a standalone phone can be used by lay personnel to measure subjective refraction. Its validity has been pilot-tested in clinical settings and underserved communities. The app estimates the refractive error by measuring the distances of far points for discerning visual stimuli. Spherical equivalent refraction and astigmatism can be measured using Tumbling E letters and grating patterns, respectively. The purpose of this paper is to describe the measurement protocols for performing subjective refraction using the app. Experimental results with 34 subjects (30 eyes for spherical equivalent and 38 eyes for astigmatism assessment) are presented. Measurement with the app was compared with standard clinical methods. The average absolute error of spherical equivalent refraction was 0.63D, and the average absolute error of astigmatism measurement was 0.28D. In addition, 22 subjects were enrolled to evaluate inter-pupillary distance (IPD) measurement with the app. The average absolute error in IPD measurement with the app was 1.2 mm. The protocol for measuring IPD with the app is also described.

Introduction

Uncorrected refractive error (URE) is a major cause of blindness and vision impairment in the world, affecting 86¹ to 116 million individuals², although it is treatable with glasses. Studies have shown that the prevalence of URE in remote areas is primarily driven by the low number of eye care professionals and the lack of an adequate health infrastructure to dispense glasses³. For instance, the prevalence of vision impairment due to URE among adults above 50 years of age in Sub-Saharan Africa is 10 times higher than that in high-income countries¹.

With the current advancements in the industry, the cost of eyeglasses has dropped to just a few US dollars. However, training eye care professionals is costly and time-consuming -- requiring years of training⁴. A recent study concluded that low per capita spending on health continues to limit meaningful integration of eye care within the broader healthcare systems, particularly in remote areas⁵. These grim realities point out the great need to make the diagnosis of URE accessible.

Thanks to their affordability, ubiquity, and validity, smartphone-based vision screening tools can play a pivotal role in vision screening efforts^{6,7,8,9,10,11,12,13}. These innovative tools may impact eye health care by providing a cost-effective and convenient solution for screening, identifying, and addressing vision issues, especially in underserved communities.

One example of such technology is the Peek Acuity app, which has made significant strides in the field of mobile vision screening. This app has been deployed to screen tens of thousands of individuals in some studies in Africa^14,15,16. By offering an efficient way to measure visual acuity, the Peek Acuity app has empowered healthcare providers to reach more people, making it a useful tool for addressing visual impairment. In addition to visual acuity, smartphone-based technologies for measuring refractive error have also been proposed and evaluated^17,18. Salmerón-Campillo et al. used a smartphone screen to present blue visual stimuli in a Badal optometer for visual acuity and refraction measurement¹⁷. Tousignant et al. tested the Netra smartphone refractor, which consists of a handheld binocular viewer with a smartphone inserted in it¹⁸. Compared with general smartphone apps, dedicated components or attachments other than smartphones in these systems may limit the accessibility of the technology because users have to purchase specially made devices.

To address the accessibility issue of mass URE screening, we have developed a smartphone-based refraction app (Figure 1), which employs computer vision and psychophysical methods to measure refractive error¹⁹. The app measures subjective refraction by finding the far points for given stimuli (tumbling E for spherical equivalent and grating for astigmatism) in myopic patients. A key feature of the app is that no specially made attachment is needed. All the processing needed to perform a measurement is carried out on-device within the app, and no cloud computing is involved. Thus, refraction can be measured without needing to connect the app to the network. With minimum training, laypersons can use the app to measure the refraction of patients if their smartphones are compatible. The accuracy of the app has been evaluated previously against standard clinical testing methods⁸. While the app may not be directly used for prescribing glasses, it has the potential to be used in myopia screening. Recently, it was successfully used in a vision screening among school students in a rural area⁹. This paper presents the protocols for using the app to measure subjective refraction.

Protocol

The study was conducted in accordance with the tenets of the Declaration of Helsinki at Mass Eye and Ear Infirmary (Boston, MA). Informed consent was obtained from all the participants. The study was approved by the local institutional review boards of Mass Eye and Ear (Boston, MA). Subject inclusion criteria were diagnosis of myopia and no other eye conditions, such as cataracts and retinal disease, according to an optometrist.

1. Measuring spherical equivalent

1. Launch the app and tap the Refraction button on the home page (Figure 1). Place the phone at least 2 m away from the patient.
2. Select button E for Tumbling E stimuli (Figure 2). Select the Eye to be measured (Left or Right) and ask the patient to cover the other eye.
3. Hold the phone with the screen facing the patient and tap the Start button. Ask the patient if he/she can tell the orientation of all the letters displayed on the phone screen.
4. If the patient cannot tell the orientation of the letters, gradually move the phone towards the patient.
5. While gradually approaching the patient, keep checking whether they can identify the letters. Stop as soon as the patient can tell the letter orientations.
6. Tap the Verify button. The true letter orientations will be shown in text on the screen. Compare them with the patient's report. If all 3 answers match, tap the Correct button to conclude the testing. If the orientation of any of the letters is not correctly reported, tap the Wrong button to redo the testing.

2. Measuring astigmatism

1. Launch the app and tap the Refraction button on the home page (Figure 1). Start from at least 2 m from the patient.
2. Select Astigm 1 stimulus, which is a clock dial pattern (upper right inset in Figure 3). The stimulus consists of a series of line groups from one spot pointing toward different directions, like a clock. Each line group includes 3 parallel fine lines.
3. Select the eye to be measured and ask the patient to cover the other eye. Hold the phone with the screen facing the patient and tap the Start button.
4. Ask the patient whether the line group in any of the directions appears as 3 separate lines. If the patient cannot see separate lines in any of the directions, gradually move the phone towards the patient.
5. Keep checking with the patient during the approaching movement. Stop as soon as the patient can see separated lines in at least one direction.
6. Select Astigm 2 stimuli, which are two grating patches in red and green colors. These patches are wider on one end than the other (lower right inset in Figure 3).
7. Rotate the phone around the axis perpendicular to the phone screen to a position where the grating is roughly the direction of the clearest line group of Astigm 1.
8. Fine-tune the phone rotation to find the best spot where the patient can see the red and green grating patches equally clearly. Once the best spot is found, tap the Point 1 button to record the first far point.
9. After Point 1 is recorded, the Astigm 2 stimulus will rotate 90˚ automatically. From the first far point (Point 1 position), keep the phone orientation and move the phone closer until the patient can see the red and green grating patches equally clearly and tell the wider end.
10. Tap the Point 2 button to record the second far point. With the two far points recorded, the app can calculate spherical refractive error and astigmatism and show the results on the screen.
11. On the result message box, tap the Save button to save the result or, if needed, the Retake button to redo the measurement.

3. Measuring inter-pupillary distance (IPD)

1. Launch the app and tap the IPD button on the home page (Figure 1). Place the phone approximately 40 cm away from the patient at eye level and ask the patient to look at the flashlight.
2. Tap the round button on the right to take a picture of the patient's face. The app will then start processing the image.
3. When two green crosshairs are plotted on the screen (Figure 4), examine if their locations are aligned with the center of the eyes. If yes, tap the Save button.
4. If either of the cross hairs is apparently not at the center of the eye, reject the measurement by tapping the Retake button to go back to step 3.2 and redo the measurement.

Results

For this study, the interface of the refraction test is shown in Figure 2. Depending on the selected stimuli, the app performs a spherical equivalent or full refraction test. When Tumbling E is selected, the app measures the spherical equivalent (Figure 2). When grating stimuli Astigma 1 or 2 is selected, the app measures refractive error, including astigmatism (Figure 3).

To demonstrate the app's effectiveness, 66 subjects (25 females) were split into 3 groups and participated in spherical equivalent, astigmatism, and IPD tests, respectively. The subject age range was from 8 years to 74 years (mean ± SD: 33.7 years ± 13.9 years).

Figure 5 shows the results of spherical equivalent measurement from a study (30 eyes) in which the app measurement was compared with the standard clinical measurement using an auto-refractor. The highest refractive error was up to -8D. Regression analysis suggests that the two methods were highly consistent, as the linear regression slope is almost 1, and the R-square of regression is 0.965. The mean absolute difference between the two methods was 0.63D, and the difference was < 1D in 80% of the cases. The Bland-Altman plot in Figure 5B shows that the 95% limits of agreement were [-1.81D, 1.58D].

Figure 6 shows the results of the astigmatism measurement study (38 eyes), in which the app measurements were compared with the standard subjective refraction measurement. The highest astigmatism was -2.25D, and the average cylinder power of those patients was -0.63D ± 0.59D. The difference (Mean ± SD) between the app and autorefractor measurements was 0.08D ± 0.41D, and the mean of absolute error was 0.28D. The Bland-Altman plot in Figure 6B shows that the 95% limits of agreement were [-0.89D, 0.73D]. Furthermore, the cylinder power of the two measurements was decomposed to two vectors, J0 and J45, based on the cylinder axis²⁰, the errors of the app were analyzed. The J0 error (mean of error and standard deviation of error spread) was -0.15D ± 0.56D, and the J45 error was 0.07D ± 0.21D.

In Figure 4, two IPD measurement cases are shown. The picture on the left side is a successful trial, and the one on the right shows a failed trial, as the crosshair of the left eye is off-center. Figure 7 shows the error of IPD measurements with the app (n=22) compared to an optometrist's clinical measurements using an IPD ruler. The range of IPD according to ruler measurement was from 58-69 mm (mean ± SD: 63.6 mm ± 3.2 mm). The error of the app was (-0.55 mm ± 1.4 mm), and the mean of absolute error was 1.2 mm.

Figure 1: Home page of vision screening app. Users can create patient records and select the test to be performed, including refraction, interpupillary distance, and visual acuity (not introduced here). Please click here to view a larger version of this figure.

Figure 2: Interface of the refraction measurement. This screenshot shows a spherical equivalent testing session. The patient uses two fingers to cover his left eye. The occlusion is minimal, as the eyebrow, nose, and mouth are all visible. Please click here to view a larger version of this figure.

Figure 3: Measuring astigmatism. In this case, the patient reported that the one-o'clock direction of Astigm 1 (upper right inset) was the sharpest. Therefore, when switching to the Astigm 2 stimulus (lower right inset), the phone needed to be tilted to search for the best spot around the one o'clock direction. Please click here to view a larger version of this figure.

Figure 4: Two cases of IPD measurement. Left: the two crosshairs align with eye centers well. The measurement can be accepted. Right: the crosshair on the left eye is apparently not at the eye center. This measurement should be discarded. Please click here to view a larger version of this figure.

Figure 5: Evaluation of results of spherical equivalent measurement. In this study, 30 eyes were measured with the app and also an autorefractor. (A) The linear regression shows that the two measurements are highly consistent (slope=1.02, R²=0.965). (B) Bland-Altman plot. The 95% limits of agreement were [1.81,1.58]. Please click here to view a larger version of this figure.

Figure 6: Evaluation of results of astigmatism measurement. (A) Box plot of error of astigmatism measurement by the app for 38 eyes. The average cylinder power of those patients was -0.63D ± 0.59D. The box represents the interquartile range, and the whiskers indicate the range of the error. The cross indicates the average of the error. There were two outliers, as marked by the circles. (B) Bland-Altman plot. The 95% limits of agreement were [-0.89, 0.73]. Please click here to view a larger version of this figure.

Figure 7: Box plot of error of IPD measurement by the app for 22 subjects. Comparing clinical measurements with an IPD ruler, the error was (-0.55 mm ± 1.4 mm). The box represents the interquartile range, and the whiskers indicate the range of the error. The cross indicates the average of the error. Please click here to view a larger version of this figure.

Discussion

Using the app, it is feasible for a person without professional optometry training to perform subjective refractive error tests. Its application in vision screening has been demonstrated in a recent eye screening study among school-aged students in a rural area⁹. Compared to the other mass vision screening methods that are solely based on visual acuity testing²¹, this app can provide measurement of refraction in terms of spherical and cylindrical error values typically used in clinics. Since the app is ready for use once installed on smartphones, this solution is highly accessible for underserved communities. Smartphones with a screen resolution higher than 400 pixels per inch and a selfie camera resolution higher than 1920 x 1080 pixels are suitable for running the refraction app. Many smartphones on the market nowadays can meet the specifications.

It can be expected that smartphone-based refraction measurement solutions can complement the service programs provided by ophthalmic clinicians and dedicated screening devices (e.g., iScreen, Spot Vision Screener)²² and are particularly suitable for low-resource countries and situations. One limitation of the app, though, is that it does not measure hyperopia using the protocol presented here. How to measure or identify hyperopia using the app is under investigation. As for strabismus assessment required in some eye screening programs, we have developed and validated another app, which can be used in vision screening in underserved communities as well^10,11,12.

Although eye prescription should not be based on the app measurement when access to eye care professionals is available, it can still be valuable in mass vision screening where non-professional personnel can join the workforce. Patients flagged with significant refractive error can be referred to eye care physicians for further examination.

Measurement accuracy is crucial for minimizing the false positive rate of referral. The following are some tips for successful measurements. Measurement with the app typically should be performed in well-lit environments (preferrable at least 300 lux). The smartphone app utilizes computer vision technologies to extract facial features, based on which the viewing distance is estimated. It is necessary to make sure that only the patient's face appears in the field of view of the phone camera. No other face, including the face of the test administrator, should appear in the selfie camera preview shown on the phone screen during the test, because the app cannot tell which is the patient. Since the app relies on facial features to estimate the viewing distance, it will be helpful for viewing distance estimation if as many facial features are visible as possible during the test. It is recommended to use a small occluder or just two fingers to cover the untested eye so that the eyebrow, nose, and mouth corner are all visible to the camera (Figure 2). At short viewing distances, the patient's face may occupy nearly the whole camera view. Testers should monitor the live image on the screen and make sure to align the camera properly so that the full face is always visible in the camera view.

IPD is an essential parameter for app-measured refraction. It can be manually entered in the patient profile in the app if known beforehand. Otherwise, IPD can be measured using the app. Without an individualized IPD, the app will use a default value, and it may cause measurement errors to a certain degree. It should be noted that imprecise convergence might affect the IPD measurement. For instance, a patient with refractive error and phoria may not properly fixate on the flashlight binocularly, as one eye may deviate. In such cases, the patient should wear glasses in the IPD test.

Testers need to understand that the test is a subjective measure of refraction, meaning that the outcome is based on patients' perception rather than analysis of eye optics as done by auto-refractors. Subjective refraction is the gold standard for prescribing eyeglasses. However, the challenge is to find the status of the best subjective perception. For spherical equivalent measurement, the criterion is based on reading 3 letters. There is a chance that patients guess some of the letters correctly while they cannot really see all the letters clearly. Multiple tests can help mitigate the issue.

In addition, patients with high astigmatism (usually higher than 2D) may not be suitable for spherical equivalent testing with the app because the current protocol with Tumbling E letters does not take letter orientation into consideration. For patients who are suspected to have strong astigmatism, a rough estimate could be found by showing the dial clock stimulus (Astigm 1) and asking the patient if one direction is much sharper than the other directions.

Astigmatism measurement is procedurally more demanding than spherical equivalent measurement because refraction for different axes needs to be determined. The key to accurate measurement is to locate the true far points for different axes, while the accurate direction of the axis is also to be determined. A good strategy is to scan the grating orientation by rotating the phone screen relatively fast while moving the phone slowly toward the patient. Moving too fast may cause overestimation because the phone may pass over the far points. Some patients tend to report they can see the grating clearly when, in fact, they can see better than very blurred images. Such premature reports cause underestimation. It is helpful to show patients what sharp stimuli look like before testing so that they can report consistently during the testing. Not understanding how to properly report the perception of the stimulus may cause significant errors, such as the outliers shown in Figure 6A. The two outliers were from one subject, who reported Point 1 too early (did not really see the separated lines of grating clearly) when his right eye was tested. He also reported Point 2 too late (he had already passed the clear point) when his left eye was tested. Thus, the incorrect far-point reports led to large errors.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Smartphone	Samsung	Galaxy	commercially available smartphone