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.

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.

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