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PupilScreen: Using Smartphones to Assess Traumatic Brain Injury

Published: 11 September 2017 Publication History

Abstract

Before a person suffering from a traumatic brain injury reaches a medical facility, measuring their pupillary light reflex (PLR) is one of the few quantitative measures a clinician can use to predict their outcome. We propose PupilScreen, a smartphone app and accompanying 3D-printed box that combines the repeatability, accuracy, and precision of a clinical device with the ubiquity and convenience of the penlight test that clinicians regularly use in emergency situations. The PupilScreen app stimulates the patient's eyes using the smartphone's flash and records the response using the camera. The PupilScreen box, akin to a head-mounted virtual reality display, controls the eyes' exposure to light. The recorded video is processed using convolutional neural networks that track the pupil diameter over time, allowing for the derivation of clinically relevant measures. We tested two different network architectures and found that a fully convolutional neural network was able to track pupil diameter with a median error of 0.30 mm. We also conducted a pilot clinical evaluation with six patients who had suffered a TBI and found that clinicians were almost perfect when separating unhealthy pupillary light reflexes from healthy ones using PupilScreen alone.

Supplementary Material

mariakakis (mariakakis.zip)
Supplemental movie, appendix, image and software files for, PupilScreen: Using Smartphones to Assess Traumatic Brain Injury

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  • (2024)Development of a Smartphone-Based System for Intrinsically Photosensitive Retinal Ganglion Cells Targeted Chromatic PupillometryBioengineering10.3390/bioengineering1103026711:3(267)Online publication date: 9-Mar-2024
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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 1, Issue 3
September 2017
2023 pages
EISSN:2474-9567
DOI:10.1145/3139486
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Received: 01 November 2017
Published: 11 September 2017
Accepted: 01 June 2017
Revised: 01 May 2017
Published in IMWUT Volume 1, Issue 3

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Author Tags

  1. Health sensing
  2. convolutional neural network
  3. pupil dilation
  4. pupillary light reflex
  5. pupillometer
  6. smartphones

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  • Research-article
  • Research
  • Refereed

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  • National Science Foundation Graduate Research Fellowship
  • ARCS Foundation

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  • (2024)JoulesEyeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314227:4(1-29)Online publication date: 12-Jan-2024
  • (2024)PupilSense: Detection of Depressive Episodes through Pupillary Response in the Wild2024 International Conference on Activity and Behavior Computing (ABC)10.1109/ABC61795.2024.10652166(01-13)Online publication date: 29-May-2024
  • (2024)Smartphone pupillometry for detection of cerebral vasospasm after aneurysmal subarachnoid hemorrhageJournal of Stroke and Cerebrovascular Diseases10.1016/j.jstrokecerebrovasdis.2024.10792233:10(107922)Online publication date: Oct-2024
  • (2023)Validation of a Smartphone Pupillometry Application in Diagnosing Severe Traumatic Brain InjuryJournal of Neurotrauma10.1089/neu.2022.051640:19-20(2118-2125)Online publication date: 1-Oct-2023
  • (2023)Racially fair pupillometry measurements for RGB smartphone cameras using the far red spectrumScientific Reports10.1038/s41598-023-40796-013:1Online publication date: 24-Aug-2023
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  • (2022)At-Home Pupillometry using Smartphone Facial Identification CamerasProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502493(1-12)Online publication date: 29-Apr-2022
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