Algorithm for pupillometric data analysis

Pupillometry is used clinically to evaluate retinal and optic nerve health by measuring pupillary function in response to light stimuli. We have developed an algorithm using murine pupillometric measurements to automate the analysis of pupillometric data. The raw data is filtered and thresholding is used to remove data caused by eye blinking, loss of pupil tracking, and/or head movement. Twelve physiologically relevant parameters are extracted from the collected data. Algorithm derived values do not deviate significantly from the manually calculated parameters (p ¿ 0.05). This algorithm can be used to establish normative values of pupillary light responses for humans, as well as wild-type and transgenic mouse strains, which can subsequently be used as reference metrics for characterizing the retinal phenotype of retinal disease. Furthermore, it will be instrumental in the assessment of functional visual recovery in humans and pre-clinical models of retinal degeneration and optic nerve disease following pharmacological or gene-based therapies.