Myopia is the most common eye problem and has been increasing so rapidly throughout the developing world. Recent studies have emerged to find the environmental factors causing the onset of the myopia in the childhood. In addition, prediction of the myopia onset and susceptibility to it in children attract a lot of attention.

A small wearable system is designed and implemented for recording environmental factors. The subjects take a weekly myopia test throughout the recording. The stored data will be sent to computer and analyzed to find the correlations between environmental factors and myopia progression. After gathering the data from large group of children, Computational models are made to estimate the myopia progression.

We considered several factors to be recorded that are head tilt, UV light exposure and visible light exposure. The relation of each factors to myopia progression are estimated using the recorded data from a large group of children.

Making a model that takes into account different behavioral and environmental factors for estimation of the onset and progression of myopia is trivial. This can be done by designing wearable devices to record continuously the environmental factors and making the computational models to estimate the myopia development in the children in order to diagnose and prevent it.