Specially developed software (app) was written for handheld electronic devices that uses the device camera and light detector for real-time monitoring of near-work distance and environmental lighting. A pilot study of this novel app employed children using tablet computers in a classroom. Measurements of face-device distance and face illuminance were obtained from two schools where tablets were used regularly. Children were divided randomly into a control group (CG) and intervention group (IG). The app was calibrated in a lab and configured to store average values every 20 seconds in a remote database. In both groups, the app recorded data only when a child’s face was present in the camera image. The app darkened the screen for the IG when the face-device distance was shorter than 40 cm. The total mean face-device distance was 36.8 ± 5.7 cm in CG and 47.2 ± 6.5 cm in IG. Children in IG had to accommodate approximately 0.6 D less when using their devices. The mean classroom face illuminance was 980 ± 350 lux in School #1 and 750 ± 400 lux in School #2. The novel method of remotely monitoring and controlling the face-device distance and illuminance can potentially open new paths for myopia prevention and myopia control.

A periodical self-monitoring of spherical refraction using smartphones may potentially allow a quicker intervention by eye care professionals to reduce myopia progression. Unfortunately, at low levels of myopia, the far point (FP) can be located far away from the eye which can make interactions with the device difficult. To partially remedy this issue, a novel method is proposed and tested wherein the longitudinal chromatic aberration (LCA) of blue light is leveraged to optically bring the FP closer to the eye. Firstly, LCA was obtained by measuring spherical refraction subjectively using blue pixels in stimuli shown on organic light-emitting diode (OLED) screens and also grey stimuli with matching luminance. Secondly, the visual acuity (VA) measured with a smartphone located at 1.0 m and 1.5 m and displaying blue optotypes was compared with that obtained clinically standard measurements. Finally, the spherical over refraction obtained in blue light with a smartphone was compared with clinical over-refraction with black and white (B&W) optotypes placed at 6 m. Mean LCA of blue OLED smartphone screens was -0.67 ± 0.11 D. No significant differences (p > 0.05) were found between the VA measured with blue optotypes on a smartphone screen and an eye chart. Mean difference between spherical over-refraction measured subjectively by experienced subjects with smartphones and the one obtained clinically was 0.08 ± 0.34 D. Smartphones using blue light can be used as a tool to detect changes in visual acuity and spherical refraction and facilitate monitoring of myopia progression.

Purpose: To evaluate the accuracy and precision of a web‐based smartphone app designed to measure sphero‐cylindrical over‐refraction. Methods: A total of 307 healthy young subjects (22.5 ± 3.4 years) underwent clinical subjective refraction. In addition to each subject's refractive correction, spherical and cylindrical errors from −1.50 to 0.00 D were randomly induced so that their sum did not exceed −2.50 D, thereby generating a clinical over‐refraction. Seven different IOS and Android‐based smartphones were used. A new app showing tripole rescaling stimuli in blue or red light was used. Each subject used one smartphone to measure their induced over‐refraction subjectively, obtaining an app over‐refraction finding. Differences between the app and clinical over‐refraction were analysed across 675 values. Results: The mean difference between the app and clinical over‐refraction in terms of power vector components ± limits of agreement was 0.17 ± 0.84 D for M ( p < 0.0001), 0.01 ± 0.42 D ( p = 0.28) for J ₀ and −0.01 ± 0.32 D ( p = 0.33) for J ₄₅ . The corresponding values for sphere and cylinder were 0.16 ± 0.80 D ( p < 0.0001) and 0.01 ± 0.85 D ( p = 0.40), respectively. The sphere and cylinder measurements obtained by the app differed from the expected values by no more than 0.50 D in 85% of cases. Conclusions: The accuracy and precision of the over‐refraction obtained by the app was slightly lower than standard clinical subjective refraction in terms of inter‐examiner repeatability and comparable to measurements obtained using objective methods. The app shows the potential to perform sphero‐cylindrical over‐refractions reliably.

Personal mobile devices such as smartphones are proving their usefulness in ever more applications in tele-eyecare. An inconvenience and potential source of error in these past approaches stemmed from the requirement for the subjects to situate their devices at a distance. The present study aims to clinically validate best corrected visual acuity (BCVA) measures carried out by a novel smartphone application "vision.app" (VisionApp Solutions S.L.) using comparative statistics against clinical measurements. BCVA was measured in both eyes of 40 subjects using vision.app which displayed a black Landolt-C optotype with crowding on a white background, and utilized a 4 forced-choice procedure for the subjects to find (by means of swiping in either of four directions) the smallest optotype size they could resolve. Results were compared to BCVA measurements taken using a standard Snellen chart placed at 20 feet (6 m). The t-test revealed no significant differences between the app- and clinically-measured VA (p = 0.478 (OD) and 0.608 (OS)), with a mean difference between clinical and app measurements of less than one line of the eye chart (-0.009 logMAR (OD) and -0.005 logMAR (OS)). A limit of agreement for a 95% confidence interval of ± 0.08 logMAR for OD and OS was found. The results show the potential use of a smartphone to measure BCVA at a handheld distance. The newly validated study results can hold major future advancements in tele-eyecare and provide eye care professionals with a reliable and accessible method to measure BCVA.

Introduction: To uncover a relationship between light exposure and myopia is complicated because of the challenging nature of measuring visually relevant illumination experienced by children. Objective: To find a methodology to measure face illuminance using a mobile device. Methods: Accuracy and precision of the mobile device’s built-in ambient light sensor were tested under three different lighting conditions: full-field, a single small light, and one mimicking typical office illumination. Face illuminance was computed in six faces with different skin reflectances using pixel values in face images captured by the device camera placed at 30 cm in front of the face. The results were compared with those obtained with a commercial light meter situated at the face. Results: The illuminance measured by the device’s ambient light sensor showed high linearity (R² > 0.99) slightly under-estimating or conversely over-estimating face illuminance with full-field or single light sources but accurate for office lighting. Face illuminance measured by the devices’ camera under indoor conditions using the new methodology showed a mean relative error of 27% and a high linearity (R² > 0.94). Conclusions: Introduction of an app can be used to assess the association between visually relevant environmental light levels and myopia progression.

To evaluate the relationship between myopia and potential "myopiagenic" digital habits (excessive screen time, near face-device distance or low ambient light level). 82 university students (21 ± 3 years) underwent a comprehensive optometric examination, including subjective refraction and axial length (AL) measurements. Digital habits were objectively measured using a mobile application (app) capturing screen time, face-device distance, ambient light level and number of interruptions larger than 20″ per day (called "events"). The collection of 40 M data points showed mean values: 57 ± 40 min of daily screen time, 355 ± 67 mm of face-device distance, 305 ± 215 lux of ambient light level and 52 ± 32 events. No correlation was found between spherical equivalent refraction (SER) and digital habits. Particularly, SER was more negative for greater screen times, nearer face-device distances, lower light levels or more events. AL was inversely correlated with SER decrease. Correlation coefficients were very weak (R < 0.14) in all cases. The app quantified smartphone-based digital habits in a university population. The study revealed weak correlations between digital habits and myopia, indicating that longer-duration studies in a greater population are needed to obtain powerful correlation coefficients.