Continuous Pupillography: A Case for Visual Health Ecosystem

TL;DR

This paper advocates for a continuous eye health monitoring ecosystem using wearable pupillography, discussing design constraints, comparing hardware options, and presenting a lightweight detection algorithm suitable for IoT devices.

Contribution

It introduces a framework for a wearable pupillography system, including design considerations, hardware comparisons, and a simple algorithm adaptable to micro-controllers.

Findings

Comparison of two mini-camera modules for pupillography

Development of a light algorithm suitable for micro-controllers

Analysis of challenges and future directions for continuous eye monitoring

Abstract

This article aims to cover pupillography, and its potential use in a number of ophthalmological diagnostic applications in biomedical space. With the ever-increasing incorporation of technology within our daily lives and an ever-growing active research into smart devices and technologies, we try to make a case for a health ecosystem that revolves around continuous eye monitoring. We tend to summarize the design constraints & requirements for an IoT-based continuous pupil detection system, with an attempt at developing a pipeline for wearable pupillographic device, while comparing two compact mini-camera modules currently available in the market. We use a light algorithm that can be directly adopted to current micro-controllers, and share our results for different lighting conditions, and scenarios. Lastly, we present our findings, along with an analysis on the challenges faced and a way ahead towards successfully building this ecosystem.