Evidence map›Paper›PMID 37177690›Full record

ArticleSensors (Basel, Switzerland)2023

Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles.

Leon Nissen, Julia Hübner, Jens Klinker, Maximilian Kapsecker, Alexander Leube, Max Schneckenburger, Stephan M Jonas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Leon NissenInstitute for Digital Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany.
Julia HübnerCarl Zeiss Vision GmbH, Turnstraße 27, 73430 Aalen, Germany.
Jens KlinkerSchool of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany.
Maximilian KapseckerInstitute for Digital Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany.ORCID 0000-0002-3907-0749
Alexander LeubeCarl Zeiss Vision GmbH, Turnstraße 27, 73430 Aalen, Germany.ORCID 0000-0002-9182-5408
Max SchneckenburgerCentre for Optical Technologies, Aalen University of Applied Science, 73430 Aalen, Germany.
Stephan M JonasInstitute for Digital Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany.ORCID 0000-0002-3687-6165

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a growing consensus in the global health community that the use of communication technologies will be an essential factor in ensuring universal health coverage of the world's population. New technologies can only be used profitably if their accuracy is sufficient. Therefore, we explore the feasibility of using Apple's ARKit technology to accurately measure the distance from the user's eye to their smartphone screen. We developed an iOS application for measuring eyes-to-phone distances in various angles, using the built-in front-facing-camera and TrueDepth sensor. The actual position of the phone is precisely controlled and recorded, by fixing the head position and placing the phone in a robotic arm. Our results indicate that ARKit is capable of producing accurate measurements, with overall errors ranging between 0.88% and 9.07% from the actual distance, across various head positions. The accuracy of ARKit may be impacted by several factors such as head size, position, device model, and temperature. Our findings suggest that ARKit is a useful tool in the development of applications aimed at preventing eye damage caused by smartphone use.

Indexed as

FaceSmartphoneDelivery of Health CareEyeaccuracyARKitdistance measurementface trackingvision assessment

Identifiers

PMID37177690
PMCPMC10181530

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.