Evidence map›Paper›PMID 39107497›Full record

ArticleCommunications medicine2024

Touchless short-wave infrared imaging for dynamic rapid pupillometry and gaze estimation in closed eyes.

Omer Ben Barak-Dror, Barak Hadad, Hani Barhum, David Haggiag, Michal Tepper, Israel Gannot, Yuval Nir

Registry-linked trialAbstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07199049 (Monitoring Eyelid Reflex, Eye Movements, and Pupil Responses in Patients Undergoing General Anesthesia), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT07199049 completednot on this mapstarted 2025, after this paper: background citation

Monitoring Eyelid Reflex, Eye Movements, and Pupil Responses in Patients Undergoing General Anesthesia: Neuro-Mimic Indicators of Anesthesia Depth

TypeobservationalSponsorBaşakşehir Çam & Sakura City HospitalRan2025 to 2026Enrolled125ConditionsGeneral Anesthesia, Intraoperative Awareness, Eye MovementsArmsNeuro-Mimic Observation Protocol
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Omer Ben Barak-DrorDepartment of Physiology and Pharmacology, Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel.
Barak HadadDepartment of Physiology and Pharmacology, Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel.
Hani BarhumSchool of Electrical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel.
David HaggiagDepartment of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel.
Michal TepperDepartment of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel.
Israel GannotDepartment of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel. gannoti@tauex.tau.ac.il.
Yuval NirDepartment of Physiology and Pharmacology, Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel. ynir@tauex.tau.ac.il.ORCID http://orcid.org/0000-0002-5433-6349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAssessments of gaze direction (eye movements), pupil size, and the pupillary light reflex (PLR) are critical for neurological examination and neuroscience research and constitute a powerful tool in diverse clinical settings ranging from critical care through endocrinology and drug addiction to cardiology and psychiatry. However, current bedside pupillometry is typically intermittent, qualitative, manual, and limited to open-eye cases, restricting its use in sleep medicine, anesthesia, and intensive care.

methodsWe combined short-wave infrared (SWIR, ~0.9-1.7μm) imaging with image processing algorithms to perform rapid (~30 ms) pupillometry and eye tracking behind closed eyelids. Forty-three healthy volunteers participated in two experiments with PLR evoked by visible light stimuli or directing eye movements towards screen targets. Imaging was performed simultaneously on one eye closed, and the other open eye serving as ground truth. Data analysis was performed with a custom approach quantifying changes in brightness around the pupil area or with a deep learning U-NET-based procedure.

resultsHere we show that analysis of SWIR imaging data can successfully measure stimulus-evoked PLR in closed-eye conditions, revealing PLR events in single trials and significant PLRs in nearly all individual subjects, as well as estimating gaze direction. The neural net-based analysis could successfully use closed-eye SWIR data to recreate estimates of open-eye images and assess pupil size.

conclusionsContinuous touchless monitoring of rapid dynamics in pupil size and gaze direction through closed eyes paves the way for developing devices with wide-ranging applications, fulfilling long-standing goals in clinical and research fields.

Identifiers

PMID39107497
PMCPMC11303404

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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.