<p>Dyschromatopsia is a disorder involving difficulty or inability to recognize color distributions and distinguish between shades of different colours in severe cases. Recently, a non-invasive algorithmic technique for its diagnosis and monitoring has been proposed. Based on these results, in this paper, the DEA (Dyschromatopsia re-Education Algorithm) algorithm for the re-education of the eye to color vision is presented through a training path that exploits brain plasticity. DEA has also been converted into an app in order to run on personal smartphones. Also, for this reason, the use of DEA can take place without the help of a professional figure. After the diagnostic phase in which type and severity of dyschromatopsia are assessed, the algorithm proceeds with eye re-education by exploiting the brain’s plastic readjustment ability. The re-education method is based on the standard artificial intelligence learning model. Eye re-education shows progressive improvement in visual color ability and color distribution. Moreover, the achieved results appear to be permanent (at least within three months after training). This study represents a proof of concept for the proposed re-educational method. The results from the pilot experimentation are promising and demonstrate the feasibility of the approach. Future studies on a larger scale, in collaboration with clinical experts, will be necessary to validate and optimize the methodology.</p>

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The innovative DEA application for color vision self-re-education of eyes suffering from dyschromatopsia

  • Alessandro Bile

摘要

Dyschromatopsia is a disorder involving difficulty or inability to recognize color distributions and distinguish between shades of different colours in severe cases. Recently, a non-invasive algorithmic technique for its diagnosis and monitoring has been proposed. Based on these results, in this paper, the DEA (Dyschromatopsia re-Education Algorithm) algorithm for the re-education of the eye to color vision is presented through a training path that exploits brain plasticity. DEA has also been converted into an app in order to run on personal smartphones. Also, for this reason, the use of DEA can take place without the help of a professional figure. After the diagnostic phase in which type and severity of dyschromatopsia are assessed, the algorithm proceeds with eye re-education by exploiting the brain’s plastic readjustment ability. The re-education method is based on the standard artificial intelligence learning model. Eye re-education shows progressive improvement in visual color ability and color distribution. Moreover, the achieved results appear to be permanent (at least within three months after training). This study represents a proof of concept for the proposed re-educational method. The results from the pilot experimentation are promising and demonstrate the feasibility of the approach. Future studies on a larger scale, in collaboration with clinical experts, will be necessary to validate and optimize the methodology.