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Continuous Pupillography: A Case for Visual Health Ecosystem

Usama Younus, Nirupam Roy

TL;DR

The design constraints&requirements for an IoT-based continuous pupil detection system are summarized, with an attempt at developing a pipeline for wearable pupillographic device, while comparing two compact mini-camera modules currently available in the market.

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.

Continuous Pupillography: A Case for Visual Health Ecosystem

TL;DR

The design constraints&requirements for an IoT-based continuous pupil detection system are summarized, with an attempt at developing a pipeline for wearable pupillographic device, while comparing two compact mini-camera modules currently available in the market.

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.

Paper Structure

This paper contains 16 sections, 1 equation, 3 figures, 2 tables.

Figures (3)

  • Figure 1: A labelled cross-sectional view of the complete eye structure. Exactly reproduced from the Medical Illustrations of EyeAnatomy
  • Figure 2: A Systematic Flow Diagram of Pupillary Response Rate and Subsequent Categorization of Various Diseases palmer2007assessment.
  • Figure 3: From Left to Right: 5MP ArduCam, ArduCam with IR Illumination, 7MP Pi Noir V2, LED Illumination Panel