ArticleClinical ophthalmology (Auckland, N.Z.)2022
Pilot Study of Smartphone Infrared Pupillography and Pupillometry.
Article in Clinical ophthalmology (Auckland, N.Z.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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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
7 citing papers in PubMed, 16 citations in OpenAlex.
- SmartPLR: a digital solution for AI-powered smartphone pupillometry.BMC ophthalmology · 2025Article
- Measuring the Pupillary Light Reflex Using Portable Instruments in Applied Settings.Vision (Basel, Switzerland) · 2024Article
- Basics, benefits, and pitfalls of pupillometers assessing visual function.Eye (London, England) · 2024Review
- Article
- Smartphone Pupillometry and Machine Learning for Detection of Acute Mild Traumatic Brain Injury: Cohort Study.JMIR neurotechnology · 2024Article
- Introduction of Deep Learning-Based Infrared Image Analysis to Marginal Reflex Distance1 Measurement Method to Simultaneously Capture Images and Compute Results: Clinical Validation Study.Journal of clinical medicine · 2023Article
- Iris Color Matters-A Contractility Analysis With Dynamic Volume-Rendered Optical Coherence Tomography Pupillometry.Translational vision science & technology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo describe and validate a novel portable smartphone-based infrared pupillographer. MATERIALS AND
methodsA prototype infrared smartphone pupillographer device was custom designed for this project. Infrared video and photo pupillography were attempted on 12 patients with different clinical pupillary examination findings. Captured pupillography media files were assessed by three masked investigators, and the agreement between their qualitative clinical evaluation was tested against the evaluation of the neuro-ophthalmologist who performed the real-time examination and pupillography. Quantitative measurements of the pupillary diameter were performed by three investigators using a custom designed smartphone application on three different smartphones and on a personal computer. Measurements obtained by the three investigators using the smartphone and the desktop computer were compared.
resultsInfrared video pupillography of high quality was successfully captured for light and near pupillary reflexes, and infrared still photographs were obtained in light and dark conditions in 23 eyes of the 12 patients. Examination findings included relative afferent pupillary defect (n = 5), normal pupillary examination (n = 4), anisocoria (n = 2), and relative afferent pupillary reflex by reverse (n = 1). There was 100% agreement in the qualitative pupillary evaluation of the masked investigators compared with real time clinical examination. Quantitative measurements of pupillary size obtained on the smartphone and desktop computer showed excellent agreement among the three investigators with intraclass correlation (ICC) coefficient ranging from 0.982-0.986 (P<0.001) and 0.995 (P<0.001) for the smartphone and the desktop computer groups, respectively. Level of agreement ranged between -0.27 and 0.32. Mean pupil diameter errors were 0.03 ± 0.15 mm between groups (P = 0.248).
conclusionThis pilot study demonstrates the feasibility of smartphone-based infrared pupillography for high quality photo and video documentation of pupillary examination at the bedside and in the clinic with accurate and reproducible measurements of the pupillary size in light and dark conditions.
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