# Automated Pupillary Light Reflex Test on a Portable Platform

## TL;DR

This paper presents a portable device and an automated algorithm for performing and analyzing pupillary light reflex tests to diagnose relative afferent pupillary defect with high accuracy.

## Contribution

The paper introduces a novel portable eye imaging device and an automated diagnostic algorithm for RAPD detection, validated with clinical data.

## Key findings

- Algorithm achieves 93.8% sensitivity.
- Algorithm achieves 87.5% specificity.
- Device enables high-resolution eye recordings in clinical settings.

## Abstract

In this paper, we introduce a portable eye imaging device denoted as lab-on-a-headset, which can automatically perform a swinging flashlight test. We utilized this device in a clinical study to obtain high-resolution recordings of eyes while they are exposed to a varying light stimuli. Half of the participants had relative afferent pupillary defect (RAPD) while the other half was a control group. In case of positive RAPD, patients pupils constrict less or do not constrict when light stimuli swings from the unaffected eye to the affected eye. To automatically diagnose RAPD, we propose an algorithm based on pupil localization, pupil size measurement, and pupil size comparison of right and left eye during the light reflex test. We validate the algorithmic performance over a dataset obtained from 22 subjects and show that proposed algorithm can achieve a sensitivity of 93.8% and a specificity of 87.5%.