Assessing the goanna visual field algorithm using artificial scotoma generation on human observers

Abstract

Purpose: To validate the performance of a new perimetric algorithm (Gradient- Oriented Automated Natural Neighbor Approach; GOANNA) in humans using a novel combination of computer simulation and human testing, which we call Artificial Scotoma Generation (ASG). Methods: Fifteen healthy observers were recruited. Baseline conventional automated perimetry was performed on the Octopus 900. Visual field sensitivity was measured using two different procedures: GOANNA and Zippy Estimation by Sequential Testing (ZEST). Four different scotoma types were induced in each observer by implementing a novel technique that inserts a step between the algorithm and the perimeter, which in turn alters presentat..