Project

VisionApp - we care for your eyes

Goal: At VisionApp (www.vision-app.eu) we develop mobile applications that care for your eyes.

Methods: Optometry, Optics, Digital Signal Processing, Programming, Android Programming, Ocular Refraction, iOS, Myopia, Smart Phone, Tablet, Java

Date: 14 June 2016

Updates
0 new
2
Recommendations
0 new
2
Followers
0 new
13
Reads
0 new
303

Project log

Matt Jaskulski
added a research item
Purpose: To evaluate under known, standarized conditions a novel app for remote monitoring of myopia progression in children. Vision professionals and researchers can use a cloud-connected web interface to remotely access their patients´ data: viewing distance, face illumination and sphero-cylindrical refraction obtained using myopia.app. Viewing distance and face illuminance during device use are synchronized in real time, every second of every day (Salmerón-Campillo et al. J.Opthalmol., 2019), while refraction can be self estimated (patent-pending) using the app and used to remotely monitor myopia progression or as a starting point for clinical subjective refraction.
Matt Jaskulski
added an update
@In the most recent scientific study by @Mark Bullimore et. al. they conclude that a 1-diopter increase in myopia is associated with a 67% increase in the prevalence of myopic maculopathy. Slowing myopia by 1 diopter should reduce the likelihood of a patient developing myopic maculopathy by 40%.
You can read the article in Optometry and Vision Scence: https://journals.lww.com/…/Myopia_Control__Why_Each_Diopter…
At the same time, the most recent pilot study with VisionApp has shown the app to relax the eye by 0.6 diopters in children using 10-inch tablets.
You can read the full article in Journal of Ophthalmology: https://www.hindawi.com/journals/joph/2019/1946073/
#visionapp #myopia #diopter #nearsightedness #research #science#optometry #optometria #ciencia #optics #optica #vision #eye
 
Matt Jaskulski
added a research item
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.
Matt Jaskulski
added a research item
Children 8 and under on average spend 2.3h with screen media daily. The average time spent daily with mobile devices has tripled since 2013. Modern mobile devices are fully suited to measure illumination and near work distance in natural conditions at hight acquisition rates. We have developed a new mobile application, called VisionApp, capable of measuring the near work distance and face illumination in real time, with high accuracy. The application works in the background so that the user can use the device in their habitual manner. A data sample (near work distance and face illumination) is stored in a cloud database every 20 seconds (180 samples every hour). The new app can serve as a research tool to track the progression of myopia in children and adolescents, and also as a myopia control tool. In the latter case the app can be configured to darken the screen when the near work distance is too close. The poster details the results of the calibration of both distance and light level measurements.
Matt Jaskulski
added an update
El profesor Norberto López-Gil , uno de los fundadores de VisionApp y Catedratico de la Universidad de Murcia impartirá una charla y un curso monográfico durante el congreso Optom 18, celebrado entre el día 13 y 15 de Abril en la Feria de Madrid. Estamos orgullosos por poder contar con la experiencia y conocimientos del profesor López-Gil, dando la prueba de que la ciencia e investigación forman la base de la tecnología, misión y excelencia de VisionApp.
 
Matt Jaskulski
added a project goal
At VisionApp (www.vision-app.eu) we develop mobile applications that care for your eyes.
 
Matt Jaskulski
added a research item
Purpose: Part of the large increase of myopia prevalence in children is due to prolonged use of electronic screens (smartphones and tablets) at near-work distances. Myopia progression is correlated with near vision. However, there are no commercially available solutions to measure work distance in natural conditions at high acquisition rates. We developed an application (VisionApp, www.vision-app.eu) for the Android OS, capable of measuring the distance between the user and the device in real time. We test its accuracy and precision. Methods: We used the front camera of two smartphones of different brands: Xiaomi Mi5s, and Samsung Galaxy S6+ to acquire images of two subjects at varying distances, at a rate of 30 FPS. The head was fixed using a chin rest. The device was mounted in a holder affixed to a stepper motor, which allowed the distance to the subject to be precisely controlled. The distance between the subject and the device was measured within the range from 190 to 420mm in 10mm steps. Three consecutive measurements were obtained at each distance in each case. Both devices were calibrated by means of applying a calibration factor CF, which accounted for differences in proprietary device parameters, such as the ratio between total and active camera sensor area. The CF was measured at 5 distances from the subject (200, 250, 300, 350 and 400mm), and found to be the same for the same device. Results: Linear fit to the smartphone-measured distance in function of real, stepper motor-controlled distance showed a slope of 1.110 (R2=0.99) and 0.978 (R2=0.99) for Xiaomi and Samsung, respectively. The mean and SD was 11±10 mm and 5±10 mm for Xiaomi and Samsung, respectively. The calibration factor CF obtained for Xiaomi was 0.87±0.03, and 1.15±0.03 for Samsung. The mean maximum CF variation for different distances was 6.5%. Conclusions: We have developed and evaluated a new app that can be used to measure the work distance between the user and the device. The main benefit is that the app runs on the very device, eliminating the need for any extra equipment. The accuracy of the distance measurement was ~1 cm. The accuracy did not depend on the model of smartphone used, nor the calibration distance (calibration can be performed at any distance and assure the same, high accuracy). The app was designed to store the measurement data in the device and can be used in parallel with other running applications. It can be a suitable tool for research or clinical studies that aim to evaluate the distance between a user and an electronic device under natural conditions.