Cargando…
At-Home Pupillometry using Smartphone Facial Identification Cameras
With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686294/ https://www.ncbi.nlm.nih.gov/pubmed/38031623 http://dx.doi.org/10.1145/3491102.3502493 |
_version_ | 1785151760312041472 |
---|---|
author | Barry, Colin De Souza, Jessica Xuan, Yinan Holden, Jason Granholm, Eric Wang, Edward Jay |
author_facet | Barry, Colin De Souza, Jessica Xuan, Yinan Holden, Jason Granholm, Eric Wang, Edward Jay |
author_sort | Barry, Colin |
collection | PubMed |
description | With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. In comparison to a gold standard pupillometer during a pupillary light reflex test, the smartphone-based system achieves a median MAE of 0.27mm for absolute pupil dilation tracking and a median error of 3.52% for pupil dilation change tracking. Additionally, we remotely deployed the system to older adults as part of a usability study that demonstrates promise for future smartphone deployments to remotely collect data in older, inexperienced adult users operating the system themselves. |
format | Online Article Text |
id | pubmed-10686294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-106862942023-11-29 At-Home Pupillometry using Smartphone Facial Identification Cameras Barry, Colin De Souza, Jessica Xuan, Yinan Holden, Jason Granholm, Eric Wang, Edward Jay Proc SIGCHI Conf Hum Factor Comput Syst Article With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. In comparison to a gold standard pupillometer during a pupillary light reflex test, the smartphone-based system achieves a median MAE of 0.27mm for absolute pupil dilation tracking and a median error of 3.52% for pupil dilation change tracking. Additionally, we remotely deployed the system to older adults as part of a usability study that demonstrates promise for future smartphone deployments to remotely collect data in older, inexperienced adult users operating the system themselves. 2022-04 2022-04-29 /pmc/articles/PMC10686294/ /pubmed/38031623 http://dx.doi.org/10.1145/3491102.3502493 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Barry, Colin De Souza, Jessica Xuan, Yinan Holden, Jason Granholm, Eric Wang, Edward Jay At-Home Pupillometry using Smartphone Facial Identification Cameras |
title | At-Home Pupillometry using Smartphone Facial Identification Cameras |
title_full | At-Home Pupillometry using Smartphone Facial Identification Cameras |
title_fullStr | At-Home Pupillometry using Smartphone Facial Identification Cameras |
title_full_unstemmed | At-Home Pupillometry using Smartphone Facial Identification Cameras |
title_short | At-Home Pupillometry using Smartphone Facial Identification Cameras |
title_sort | at-home pupillometry using smartphone facial identification cameras |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686294/ https://www.ncbi.nlm.nih.gov/pubmed/38031623 http://dx.doi.org/10.1145/3491102.3502493 |
work_keys_str_mv | AT barrycolin athomepupillometryusingsmartphonefacialidentificationcameras AT desouzajessica athomepupillometryusingsmartphonefacialidentificationcameras AT xuanyinan athomepupillometryusingsmartphonefacialidentificationcameras AT holdenjason athomepupillometryusingsmartphonefacialidentificationcameras AT granholmeric athomepupillometryusingsmartphonefacialidentificationcameras AT wangedwardjay athomepupillometryusingsmartphonefacialidentificationcameras |