ArticleJournal of clinical monitoring and computing2021
Feasibility study of a smartphone pupillometer and evaluation of its accuracy.
Article in Journal of clinical monitoring and computing, 2021. 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, 16 citations in OpenAlex.
- Pharmacological and light-driven pupillary accommodation in guinea pigs: comparative effects of muscarinic modulators and illumination across developmental stages.International journal of ophthalmology · 2026Article
- SmartPLR: a digital solution for AI-powered smartphone pupillometry.BMC ophthalmology · 2025Article
- Video-based pupillometry using Fourier Mellin image correlation.Scientific reports · 2025Article
- Observational
- Racially fair pupillometry measurements for RGB smartphone cameras using the far red spectrum.Scientific reports · 2023Article
- At-Home Pupillometry using Smartphone Facial Identification Cameras.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2022Article
- Pilot Study of Smartphone Infrared Pupillography and Pupillometry.Clinical ophthalmology (Auckland, N.Z.) · 2022Article
- Interdevice Agreement between a Smartphone and a Commercial Pupillometer.International journal of applied & basic medical researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Measurement of pupillary characteristics, such as pupillary unrest in ambient light, and reflex dilation have been shown to be useful in a variety of clinical situations. Dedicated pupillometers typically capture images in the near-infrared to allow imaging in both light and darkness. However, because a subset of pupillary measurements can be acquired with levels of visible light suitable for conventional cameras, it is theoretically possible to capture data using general purpose cameras and computing devices such as those found on smartphones. Here we describe the development of a smartphone-based pupillometer and compare its performance with a commercial pupillometer. Smartphone pupillometry software was developed and then compared with a commercial pupillometer by performing simultaneous scans in both eyes, using the smartphone pupillometer and a commercial pupillometer. The raw scans were compared, as well as a selected pupillary index: pupillary unrest in ambient light. In 77% of the scans the software was able to successfully identify the pupil and iris. The raw data as well as calculated values of pupillary unrest in ambient light were in clinically acceptable levels of agreement; Bland-Altman analysis of raw pupil measurements yielded a 95% confidence interval of 0.26 mm. In certain situations a smartphone pupillometer may be an appropriate alternative to a commercial pupillometer.
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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.