At-Home Pupillometry using Smartphone Facial Identification Cameras.
Proc SIGCHI Conf Hum Factor Comput Syst
; 20222022 Apr.
Article
em En
| MEDLINE
| ID: mdl-38031623
ABSTRACT
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.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Proc SIGCHI Conf Hum Factor Comput Syst
Ano de publicação:
2022
Tipo de documento:
Article