The refraction testing app was developed with support in part from NIH grant EY034345 and the Harvard Catalyst award (National Center for Advancing Translational Sciences, NIH Award UL1 TR002541). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, or the NIH.

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
<ol>
	<li>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.</li>
	<li>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.</li>
	<li>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.</li>
	<li>If the patient cannot tell the orientation of the letters, gradually move the phone towards the patient.</li>
	<li>While gradually approaching the patient, keep checking whether they can identify the letters. Stop as soon as the patient can tell the letter orientations.</li>
	<li>Tap the Verify button. The true letter orientations will be shown in text on the screen. Compare them with the patient&#39;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.</li>
</ol>
2. Measuring astigmatism
<ol>
	<li>Launch the app and tap the Refraction button on the home page (Figure 1). Start from at least 2 m from the patient.</li>
	<li>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.</li>
	<li>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.</li>
	<li>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.</li>
	<li>Keep checking with the patient&#160;during the approaching movement. Stop as soon as the patient can see separated lines in at least one direction.</li>
	<li>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).</li>
	<li>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.</li>
	<li>Fine-tune the phone rotation to find the best spot where the patient&#160;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.</li>
	<li>After Point 1 is recorded, the Astigm 2 stimulus will rotate 90&#730; 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.</li>
	<li>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.</li>
	<li>On the result message box, tap the Save button to save the result or, if needed, the Retake button to redo the measurement.</li>
</ol>
3. Measuring inter-pupillary distance (IPD)
<ol>
	<li>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.</li>
	<li>Tap the round button on the right to take a picture of the patient&#39;s face. The app will then start processing the image.</li>
	<li>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.</li>
	<li>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.</li>
</ol>

Smartphone App for Measuring Refractive Errors and Inter-Pupillary Distance

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<li>Pundlik, S., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Preliminary+evaluation+of+a+mobile+device+for+dark+adaptation+measurement%5BTitle%5D)+AND+%22Transl+Vis+Sci+Technol%22%5BJournal%5D)">Preliminary evaluation of a mobile device for dark adaptation measurement.</a> Transl Vis Sci Technol. 8 (1), 1-11 (2019).</li>
<li>Pundlik, S., Shivshanker, P., Nigalye, A., Luo, G., Husain, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluation+of+a+mobile+app+for+dark+adaptation+measurement+in+individuals+with+age-related+macular+degeneration%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Evaluation of a mobile app for dark adaptation measurement in individuals with age-related macular degeneration.</a> Sci Rep. 13 (1), 22191(2023).</li>
<li>Luo, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Preliminary+evaluation+of+a+smartphone+app+for+refractive+error+measurement%5BTitle%5D)+AND+%22Transl+Vis+Sci+Technol%22%5BJournal%5D)">Preliminary evaluation of a smartphone app for refractive error measurement.</a> Transl Vis Sci Technol. 11 (2), 40(2022).</li>
<li>Wang, Z., Kempen, J., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Using+smartphones+to+enhance+vision+screening+in+rural+areas%3A+Pilot+study%5BTitle%5D)+AND+%22JMIR+Format+Research%22%5BJournal%5D)">Using smartphones to enhance vision screening in rural areas: Pilot study.</a> JMIR Format Research. 8, e55270(2024).</li>
<li>Pundlik, S., Tomasi, M., Liu, R., Houston, K., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Development+and+preliminary+evaluation+of+a+smartphone+app+for+measuring+eye+alignment%5BTitle%5D)+AND+%22Transl+Vis+Sci+Technol%22%5BJournal%5D)">Development and preliminary evaluation of a smartphone app for measuring eye alignment.</a> Transl Vis Sci Technol. 8 (1), 19(2019).</li>
<li>Luo, G., Pundlik, S., Tomasi, M., Houston, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Using+an+automated+Hirschberg+test+App+to+evaluate+ocular+alignment%5BTitle%5D)+AND+%22J+Vis+Exp%22%5BJournal%5D)">Using an automated Hirschberg test App to evaluate ocular alignment.</a> J Vis Exp. (157), e60908(2020).</li>
<li>Cheng, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+smartphone+ocular+alignment+measurement+app+in+school+screening+for+strabismus%5BTitle%5D)+AND+%22BMC+Ophthalmol%22%5BJournal%5D)">A smartphone ocular alignment measurement app in school screening for strabismus.</a> BMC Ophthalmol. 21 (1), 150(2021).</li>
<li>Marusic, S., Luo, G., Raghuram, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Myopia+screening+smartphone+App%3A+Validity+in+assessing+refractive+error+in+a+pediatric+cohort%5BTitle%5D)+AND+%22Invest+Ophthalmol+Vis+Sci%22%5BJournal%5D)">Myopia screening smartphone App: Validity in assessing refractive error in a pediatric cohort.</a> Invest Ophthalmol Vis Sci. 63 (7), 1447-F0405 (2022).</li>
<li>Andersen, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Implementing+a+school+vision+screening+program+in+Botswana+using+smartphone+technology%5BTitle%5D)+AND+%22Telemed+e-Health%22%5BJournal%5D)">Implementing a school vision screening program in Botswana using smartphone technology.</a> Telemed e-Health. 26 (2), 255-258 (2020).</li>
<li>Manus, M., van der Linde, J., Kuper, H., Olinger, R., Swanepoel De, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Community-based+hearing+and+vision+screening+in+schools+in+low-income+communities+using+mobile+health+technologies%5BTitle%5D)+AND+%22Lang+Speech+Hear+Serv+Sch%22%5BJournal%5D)">Community-based hearing and vision screening in schools in low-income communities using mobile health technologies.</a> Lang Speech Hear Serv Sch. 52 (2), 568-580 (2021).</li>
<li>Eksteen, S., Eikelboom, R. H., Kuper, H., Launer, S., Swanepoel, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Prevalence+and+characteristics+of+hearing+and+vision+loss+in+preschool+children+from+low+income+South+African+communities%3A+results+of+a+screening+program+of+10%2C390+children%5BTitle%5D)+AND+%22BMC+Pediat%22%5BJournal%5D)">Prevalence and characteristics of hearing and vision loss in preschool children from low income South African communities: results of a screening program of 10,390 children.</a> BMC Pediat. 22 (1), 22(2022).</li>
<li>Salmerón-Campillo, R. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Measuring+visual+acuity+and+spherical+refraction+with+smartphone+screens+emitting+blue+light%5BTitle%5D)+AND+%22J+Optomet%22%5BJournal%5D)">Measuring visual acuity and spherical refraction with smartphone screens emitting blue light.</a> J Optomet. 17 (1), 100494(2024).</li>
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<li>Measuring eye refraction. US patent. , 11903644 (2024).</li>
<li>Thibos, L. N., Wheeler, W., Horner, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Power+vectors%3A+An+application+of+Fourier+analysis+to+the+description+and+statistical+analysis+of+refractive+error%5BTitle%5D)+AND+%22Optomet+Vis+Sci%22%5BJournal%5D)">Power vectors: An application of Fourier analysis to the description and statistical analysis of refractive error.</a> Optomet Vis Sci. 74 (6), 367-375 (1997).</li>
<li>Lundh, B. I., Derefeldt, G., Nyberg, S., Lennerstrand, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Picture+simulation+of+contrast+sensitivity+in+organic+and+functional+amblyopia%5BTitle%5D)+AND+%22Acta+Ophthalmol%22%5BJournal%5D)">Picture simulation of contrast sensitivity in organic and functional amblyopia.</a> Acta Ophthalmol. 59 (5), 774-783 (1981).</li>
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</ol>

Gang Luo has a patent related to refraction measurement. Gang Luo and Shrinivas Pundlik are two of the co-founders of EyeNexo LLC, which is a startup company developing smartphone apps for vision tests. No financial conflict of interest for the other authors.

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...

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 efforts6,7,8,9,10,11,12,13. 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 Africa14,15,16. 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 evaluated17,18. Salmer&#243;n-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.

<table><tbody><tr><td>Smartphone</td><td>Samsung</td><td>Galaxy</td><td>commercially available smartphone</td></tr></tbody></table>

subjective refraction test using a smartphone for vision screening

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.

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&#39;s eff...

Subjective Refraction Test Using a Smartphone for Vision Screening

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

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing ...

subjective-refraction-test-using-a-smartphone-for-vision-screening

Research

JoVE Journal

Medicine

607 Views.  Schepens Eye Research Institute, Mass Eye & Ear. We hebben mobiele gezondheidstechnologie ontwikkeld om de problemen op het gebied van toegankelijkheid, ongelijkheid en gelijkheid in oogzorg aan te pakken. In dit artikel laten we zien hoe u onze mobiele app kunt gebruiken om de pupilafstand, sferische equivalente breking en stigmatisme te meten. Ongecorrigeerde brekingsfout is een belangrijke oorzaak van slechtziendheid in de wereld.In achtergestelde gebieden, landelijke gebieden, gebieden met lage i...

Video: Subjectieve refractietest met behulp van een smartphone voor visusscreening

Stereoacuity Improvement using Random-Dot Video Games

Conventional amblyopia therapy involves occlusion or penalization of the dominant eye, though these methods enhance stereoscopic visual acuity in fewer than 30% of cases. To improve these results, we propose a treatment in the form of a video game, using random-dot stimuli and perceptual learning techniques to stimulate stereoacuity. The protocol is defined for stereo-deficient patients between 7-14 years of age who have already received treatment for amblyopia and have a monocular best corrected distance visual acuity of at least 0.1 logMAR. Patients are required to complete a perceptual learning program at home using the video game. While compliance is stored automatically in the cloud, periodic optometry center visits are used to track patient evolution and adjust the game&#39;s stereoscopic demand until the smallest detectable disparity is achieved. The protocol has proved to be successful, and effectiveness is gauged in terms of a two-level gain on a random stereoacuity test (global stereoacuity or cyclopean stereoacuity reference test). Moreover, the random-dot stimuli learning transfers to medial lateral stereoscopic acuity according to a Wirt Circles test, in which success criteria is a final stereoacuity of over 140&#34;, and the attained enhancement corresponds to no less than two levels of stereoscopic acuity. Six months later, a random-dot stereoacuity test recorded no reduction in the stereoacuity that was achieved.

Presented here is a protocol to improve stereoacuity using gamified perceptual learning software based on random-dot stimuli. Patients are stereo-deficient subjects without strabismus. The protocol combines optometry center visits with home exercises using software. Compliance and stereoacuity evolution are stored in the cloud.

Conventional amblyopia therapy involves occlusion or penalization of the dominant eye, though these methods enhance stereoscopic visual acuity in fewer ...

Behavior

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Macular degeneration typically results in heterogeneous binocular central visual defects. Currently available approaches to assess central visual field, like the microperimetry, can test only one eye at a time. Therefore, they cannot explain how the defects in each eye affect the binocular interaction and real-world function. Dichoptic stimulus presentation with a gaze-controlled system could provide a reliable measure of monocular/binocular visual fields. However, dichoptic stimulus presentation and simultaneous eye-tracking are challenging because optical devices of instruments that present stimulus dichoptically (e.g., haploscope) always interfere with eye-trackers (e.g., infrared video-based eye-trackers). Therefore, the goals were 1) to develop a method for dichoptic stimulus presentation with simultaneous eye-tracking, using 3D-shutter glasses and 3D-ready monitors, that is not affected by interference and 2) to use this method to develop a protocol for assessing central visual field in subjects with central vision loss. The results showed that this setup provides a practical solution for reliably measuring eye-movements in dichoptic viewing condition. In addition, it was also demonstrated that this method can assess gaze-controlled binocular central visual field in subjects with central vision loss.

Presented here is a protocol for assessing binocular eye movements and gaze-controlled central visual field screening in participants with central vision loss.

Macular degeneration typically results in heterogeneous binocular central visual defects. Currently available approaches to assess central visual field, ...

An Automated Assessment of Visual Acuity in Infants and Toddlers

An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Visual acuity measurement is an important visual function test to perform in infancy and childhood. However, accurate visual acuity measurement in infants is difficult because of deficiencies in their communication ability. This paper presents a novel automated method to assess visual acuity in children (5-36 months old). This method, the automated acuity card procedure (AACP), uses a webcam for eye tracking and recognizes children's watching behaviors automatically. A two-choice preferential-looking test is performed when the tested child watches the visual stimuli shown on a high-resolution digital display screen. When the tested child watches the stimuli, their facial pictures are recorded by the webcam. These pictures are used by the set computer program to analyze their watching behavior. With this procedure, the child's eye movement responses to different stimuli are measured, and their visual acuity is assessed without communication. By comparing the results with grating acuity obtained by Teller Acuity Cards (TACs), AACP performance is deemed comparable to that of TACs.

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System  

In this paper, we present a novel automated method for assessing visual acuity in infants and toddlers by using an eye-tracking system.

Visual acuity measurement is an important visual function test to perform in infancy and childhood. However, accurate visual acuity measurement in infants ...

Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases

The retinal pigment epithelium (RPE) is juxtaposed to the overlying sensory retina, and supports the function of the visual system. Among the tasks performed by the RPE are phagocytosis and processing of outer photoreceptor segments through lysosome-derived organelles. These degradation products, stored and referred to as lipofuscin granules, are composed partially of bisretinoids, which have broad fluorescence absorption and emission spectra that can be detected clinically as fundus autofluorescence with confocal scanning laser ophthalmoscopy (cSLO). Lipofuscin accumulation is associated with increasing age, but is also found in various patterns in both acquired and inherited degenerative diseases of the retina. Thus, studying its pattern of accumulation and correlating such patterns with changes in the overlying sensory retina are essential to understanding the pathophysiology and progression of retinal disease. Here, we describe a technique employed by our lab and others that uses cSLO in order to quantify the level of RPE lipofuscin in both healthy and diseased eyes.

The retinal pigment epithelium (RPE) supports the sensory retina through recycling visual cycle byproducts, which accumulate as lipofuscin. These products are autofluorescent and can be qualitatively imaged in vivo. Here, we describe a method to quantitatively image RPE lipofuscin using confocal scanning laser ophthalmoscopy.

The retinal pigment epithelium (RPE) is juxtaposed to the overlying sensory retina, and supports the function of the visual system. Among the tasks ...

Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to assess human gait. The primary aim of this manuscript is to test the concurrent validity of kinematic measures recorded by a smartphone application in comparison to a 3D motion capture system in the sagittal plane. The secondary aim was to develop a protocol for clinicians on the set up of the smartphone camera for video movement analysis.
The sagittal plane knee angle was measured during heel strike and toe off events using the smart phone app and a 3D motion-capture system in 32 healthy subjects. Three trials were performed at near (2-m) and far (4-m) smartphone camera distances. The order of the distances was randomized. Regression analysis was performed to estimate the height of the camera based on either the subject&#39;s height or leg length.
Absolute measurement errors were least during toe off (3.12 &#177; 5.44 degrees) compared to heel strike (5.81 &#177; 5.26 degrees). There were significant (p &#60; 0.05) but moderate agreements between the application and 3D motion capture measures of knee angles. There were also no significant (p &#62; 0.05) differences between the absolute measurement errors between the two camera positions. The measurement errors averaged between 3 - 5 degrees during toe off and heel strike events of the gait cycle.
The use of smartphone apps can be a useful tool in the clinic for performing gait or human movement analysis. Further studies are needed to establish the accuracy in measuring movements of the upper extremity and trunk.

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

This manuscript describes the method to test the concurrent validity of kinematic measures recorded by the smartphone application in comparison to a 3D motion capture system in the sagittal plane. This protocol will enable clinicians to set up smartphones for video capture of human movement.

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to ...

Smartphone Fundus Photography

Smartphone fundus photography is a simple technique to obtain ocular fundus pictures using a smartphone camera and a conventional handheld indirect ophthalmoscopy lens. This technique is indispensable when picture documentation of optic nerve, retina, and retinal vessels is necessary but a fundus camera is not available. The main advantage of this technique is the widespread&#160;availability of smartphones that allows documentation of macula and optic nerve changes in many settings that was not previously possible. Following the well-defined steps detailed here, such as proper alignment of the phone camera, handheld lens, and the patient&#39;s pupil, is the key for obtaining a clear retina picture with no interfering light reflections and aberrations. In this paper, the optical principles of indirect ophthalmoscopy and fundus photography will be reviewed first. Then, the step-by-step method to record a good quality retinal image using a smartphone will be explained.

Fundus photography normally requires specialized fundus cameras that are not always available in all clinical settings.&#160;Here, a simple method to record ocular fundus images using a smartphone camera and a conventional high-plus handheld indirect ophthalmoscopy lens is described.

Smartphone fundus photography is a simple technique to obtain ocular fundus pictures using a smartphone camera and a conventional handheld indirect ...

Quantification of Oculomotor Responses and Accommodation Through Instrumentation and Analysis Toolboxes

Through the purposeful stimulation and recording of eye movements, the fundamental characteristics of the underlying neural mechanisms of eye movements can be observed. VisualEyes2020 (VE2020) was developed based on the lack of customizable software-based visual stimulation available for researchers that does not rely on motors or actuators within a traditional haploscope. This new instrument and methodology have been developed for a novel haploscope configuration utilizing both eye tracking and autorefractor systems. Analysis software that enables the synchronized analysis of eye movement and accommodative responses provides vision researchers and clinicians with a reproducible environment and shareable tool. The Vision and Neural Engineering Laboratory&#39;s (VNEL) Eye Movement Analysis Program (VEMAP) was established to process recordings produced by VE2020&#39;s eye trackers, while the Accommodative Movement Analysis Program (AMAP) was created to process the recording outputs from the corresponding autorefractor system. The VNEL studies three primary stimuli: accommodation (blur-driven changes in the convexity of the intraocular lens), vergence (inward, convergent rotation and outward, divergent rotation of the eyes), and saccades (conjugate eye movements). The VEMAP and AMAP utilize similar data flow processes, manual operator interactions, and interventions where necessary; however, these analysis platforms advance the establishment of an objective software suite that minimizes operator reliance. The utility of a graphical interface and its corresponding algorithms allow for a broad range of visual experiments to be conducted with minimal required prior coding experience from its operator(s).

VisualEyes2020 (VE2020) is a custom scripting language that presents, records, and synchronizes visual eye movement stimuli. VE2020 provides stimuli for conjugate eye movements (saccades and smooth pursuit), disconjugate eye movements (vergence), accommodation, and combinations of each. Two analysis programs unify the data processing from the eye tracking and accommodation recording systems.

Through the purposeful stimulation and recording of eye movements, the fundamental characteristics of the underlying neural mechanisms of eye movements ...

Bioengineering

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Recently, the isolated-check visual evoked potential (icVEP) technique was designed and has been reported to detect glaucomatous damage earlier and faster. It creates low spatial frequency/high temporal frequency bright stimuli and records cortical activity initiated primarily by afferents in the magnocellular ON pathway. This pathway contains neurons with larger volumes and axonal diameters, and it is preferentially damaged in early glaucoma, which can result in visual field loss. The study presented here uses standard operative procedures (SOP) of icVEP to obtain reliable results. It can detect visual function loss using a signal-to-noise ratio (SNR) corresponding to the defects of retinal nerve fiber layer (RNFL) in early stage open-angle glaucoma (OAG). A setting of 10 Hz and condition of 15% positive-contrast (bright) are selected to differentiate OAG patients and control subjects, with each check containing eight runs. Each run persists for 2 s (for 20 total cycles). A flowchart is constructed, which consists of pupil size and intraocular pressure over a 30 min rest period before each examination. Additionally, the testing order of eyes is performed to obtain reliable electroencephalographic signals. VEPs are recorded and analyzed automatically by software, and SNRs are derived based on a multivariate statistic. An SNR of &#8804; 1 is considered abnormal. A receiver-operating-characteristic (ROC) curve is applied to analyze the accuracy of group classification. Then, the SOP is applied in a cross-sectional study, showing that icVEP can detect glaucomatous visual function abnormality in the central visual field in the form of SNR. This value also correlates with the thickness thinning of RNFL and produces high classification accuracy for early stage OAG. Thus, it serves as a useful and objective diagnostic technology for the early detection of glaucoma.

The isolated-check visual evoked potential (icVEP) method is implemented here to assess the magnocellular ON pathway that is initially damaged in glaucoma. The study shows standard operative procedures using icVEP to obtain reliable results. It is proved to serve as a useful objective diagnosing technology for the early detection of glaucoma.

Recently, the isolated-check visual evoked potential (icVEP) technique was designed and has been reported to detect glaucomatous damage earlier and ...

Neuroscience

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

A smartphone app has been developed to perform the automated photographic Hirschberg test for objective measurement of ocular misalignment. By computing the difference in corneal reflection generated by the phone camera flash relative to the iris center based on high resolution images, the app can measure misalignment with a much higher precision than the naked eye performing the Hirschberg test. It has been validated in a previous clinical evaluation study by comparing to the clinical gold standard-prism and alternate cover test. The goal of this article is to describe the testing techniques regarding how to use the app to measure ocular alignment for different fixation distances, without or with cover to break fusion, as well as angle kappa, so that users can use the app to perform equivalent tests typically done in clinic using prisms.

We present a protocol of using a smartphone app to perform Hirschberg test for measuring manifest and intermittent ocular misalignment (strabismus) under near and far fixation conditions.

A smartphone app has been developed to perform the automated photographic Hirschberg test for objective measurement of ocular misalignment. By computing ...

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Current clinical visual assessment mainly focuses on static vision. However, static vision may not sufficiently reflect real-life visual function as moving optotypes are frequently observed daily. Dynamic visual acuity (DVA) might reflect real-life situations better, especially when objects are moving at high speeds. Myopia impacts static uncorrected distance visual acuity, conveniently corrected with eyeglasses. However, due to peripheral defocus and prism effects, eyeglass correction might affect DVA. The present research demonstrates a standard method to examine eyeglass-corrected DVA in myopia patients, and aimed to explore the influence of eyeglass correction on DVA. 
Initially, standard subjective refraction was performed to provide the eyeglass prescription to correct the refractive error. Then, binocular distance vision-corrected DVA was examined using the object-moving DVA protocol. Software was designed to display the moving optotypes according to the preset velocity and size on a screen. The optotype was the standard logarithmic visual chart letter E and moves from the middle of the left to the right side horizontally during the test. Moving optotypes with randomized opening direction for each size are displayed. The subjects were required to identify the opening direction of the optotype, and the DVA is defined as the minimum optotype that subjects could recognize, calculated according to the algorithm of logarithmic visual acuity.
Then, the method was applied in 181 young myopic subjects with eyeglass-corrected-to-normal static visual acuity. Dominant eye, cycloplegic subjective refraction (sphere and cylinder), accommodation function (negative and positive relative accommodation, binocular cross-cylinder), and binocular DVA at 40 and 80 degrees per second (dps) were examined. The results showed that with increasing age, DVA first increased and then decreased. When myopia was fully corrected with eyeglasses, a worse binocular DVA was associated with more significant myopic refractive error. There was no correlation between the dominant eye, accommodation function, and binocular DVA.

The present research demonstrates a method to accurately examine dynamic visual acuity (DVA) in myopic subjects with eyeglass correction. Further analysis indicated that the closer the refraction state to emmetropia, the better the eyeglass-corrected binocular DVA is at both 40 and 80 degrees per second.

Current clinical visual assessment mainly focuses on static vision. However, static vision may not sufficiently reflect real-life visual function as ...

Subjective Refraction Test Using a Smartphone for Vision Screening

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