ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2022
At-Home Pupillometry using Smartphone Facial Identification Cameras.
Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 22 citations in OpenAlex.
- Smartphone-based vestibular & gait analysis for remote fall risk assessment.Frontiers in digital health · 2026Article
- AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma.NPJ digital medicine · 2025Article
- Teledermatology to Support Self-Care in Chronic Spontaneous Urticaria.JMIR dermatology · 2025Article
- SmartPLR: a digital solution for AI-powered smartphone pupillometry.BMC ophthalmology · 2025Article
- Associations Between Blunted Pupillary Constriction and Dilation in Individuals with Schizophrenia: Evidence of a Common Mechanism?Schizophrenia bulletin open · 2025Article
- HCI and Older Adults: The Critical Turn and What Comes Next.Foundations and trends in human computer interaction · 2025Article
- Comparison of an AI-based mobile pupillometry system and NPi-200 for pupillary light reflex and correlation with glaucoma-related markers.Frontiers in neurology · 2024Article
- Racially fair pupillometry measurements for RGB smartphone cameras using the far red spectrum.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.