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Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181530/ https://www.ncbi.nlm.nih.gov/pubmed/37177690 http://dx.doi.org/10.3390/s23094486 |
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author | Nissen, Leon Hübner, Julia Klinker, Jens Kapsecker, Maximilian Leube, Alexander Schneckenburger, Max Jonas, Stephan M. |
author_facet | Nissen, Leon Hübner, Julia Klinker, Jens Kapsecker, Maximilian Leube, Alexander Schneckenburger, Max Jonas, Stephan M. |
author_sort | Nissen, Leon |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10181530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101815302023-05-13 Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles Nissen, Leon Hübner, Julia Klinker, Jens Kapsecker, Maximilian Leube, Alexander Schneckenburger, Max Jonas, Stephan M. Sensors (Basel) Article 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. MDPI 2023-05-05 /pmc/articles/PMC10181530/ /pubmed/37177690 http://dx.doi.org/10.3390/s23094486 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Nissen, Leon Hübner, Julia Klinker, Jens Kapsecker, Maximilian Leube, Alexander Schneckenburger, Max Jonas, Stephan M. Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title | Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title_full | Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title_fullStr | Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title_full_unstemmed | Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title_short | Towards Preventing Gaps in Health Care Systems through Smartphone Use: Analysis of ARKit for Accurate Measurement of Facial Distances in Different Angles |
title_sort | towards preventing gaps in health care systems through smartphone use: analysis of arkit for accurate measurement of facial distances in different angles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181530/ https://www.ncbi.nlm.nih.gov/pubmed/37177690 http://dx.doi.org/10.3390/s23094486 |
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