EVIN, an adaptive, comprehensive application to support home-based visual training for children with low vision.

Abstract

Low vision is a visual impairment that cannot be improved by standard vision aids such as glasses. Therefore, to improve their visual skills, people affected by low vision usually follow a visual training program planned and supervised by an expert in this field. Visual training is especially suitable for children because of their plasticity for learning. However, due to a lack of experts specializing in this field, training sessions are usually less frequent than optimal. As a result, home-based visual training has emerged as a solution to mitigate this problem because it can be undertaken by experts and families together. Therefore, we implemented the Visual Stimulation on the Internet (EVIN) application, which provides comprehensive visual training tasks through games. In addition, it provides reports on children’s performance in these visual training tasks. However, although EVIN has already proven its usefulness in previous works, two main solutions are needed: (i) some kind of support setup in EVIN to help experts and families work together because, among other things, of the large variety of exercises and different configurations that can be prescribed to the child and (ii) a rigorous experimental design to compare children trained with EVIN with children trained with traditional materials. To face these challenges, we present an adaptive version of EVIN that provides a new design tool that allows expert to plan visual training tasks through templates in advance. In addition, we developed new metrics and reports to achieve a more accurate assessment of children’s improvement. Among other results, it allowed us to develop an authoritative experiment to evaluate significant improvements in those children trained with EVIN.