Techniques and Equipment for Automated Pupillometry and its Application to Aid in the Diagnosis of Diseases: A Literature Review

This work aims to investigate, by means of a Systematic Literature Review, to evaluate the current state of the use of artificial intelligence in automated pupillometric technology and its application in helping to diagnose diseases, to identify the methods and equipment used and propose case new equipment based on computer vision is feasible. We also investigated the accuracy of methodologies and equipment that use computerized pupilometry to identify pathologies or disorders, as well as the viability and usability of existing pupilometers. In this sense, creating a pupilometer capable of stimulating and varying wavelengths, providing an interface to preview the exam, and embedding the classification algorithms is a great challenge. In this systematic review of the literature, we consider publications from the last ten years (2010 - 2020) indexed by seven solid scientific databases. The review identified a vast amount of work on pupillometry; however, a small amount related to the construction and viability of a pupilometer with an embedded system, easy to use and with a preview interface. Having identified this, we propose a new methodology for the construction of the pupilometer as well as the algorithm for extracting the characteristics through pupilometry.