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Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research
Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799357/ https://www.ncbi.nlm.nih.gov/pubmed/29404692 http://dx.doi.org/10.1007/s10916-018-0905-x |
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author | Siena, Francesco Luke Byrom, Bill Watts, Paul Breedon, Philip |
author_facet | Siena, Francesco Luke Byrom, Bill Watts, Paul Breedon, Philip |
author_sort | Siena, Francesco Luke |
collection | PubMed |
description | Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including robotics, automation, and medical systems. One of the most prominent areas is the production of interactive solutions for rehabilitation which includes gait analysis and facial tracking. Advancements in depth camera technology has resulted in a noticeable increase in the integration of these technologies into portable platforms, suggesting significant future potential for pervasive in-clinic and field based health assessment solutions. This paper reviews the Intel RealSense technology’s technical capabilities and discusses its application to clinical research and includes examples where the Intel RealSense camera range has been used for the measurement of health outcomes. This review supports the use of the technology to develop robust, objective movement and mobility-based endpoints to enable accurate tracking of the effects of treatment interventions in clinical trials. |
format | Online Article Text |
id | pubmed-5799357 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-57993572018-02-12 Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research Siena, Francesco Luke Byrom, Bill Watts, Paul Breedon, Philip J Med Syst Mobile & Wireless Health Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including robotics, automation, and medical systems. One of the most prominent areas is the production of interactive solutions for rehabilitation which includes gait analysis and facial tracking. Advancements in depth camera technology has resulted in a noticeable increase in the integration of these technologies into portable platforms, suggesting significant future potential for pervasive in-clinic and field based health assessment solutions. This paper reviews the Intel RealSense technology’s technical capabilities and discusses its application to clinical research and includes examples where the Intel RealSense camera range has been used for the measurement of health outcomes. This review supports the use of the technology to develop robust, objective movement and mobility-based endpoints to enable accurate tracking of the effects of treatment interventions in clinical trials. Springer US 2018-02-05 2018 /pmc/articles/PMC5799357/ /pubmed/29404692 http://dx.doi.org/10.1007/s10916-018-0905-x Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Mobile & Wireless Health Siena, Francesco Luke Byrom, Bill Watts, Paul Breedon, Philip Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title | Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title_full | Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title_fullStr | Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title_full_unstemmed | Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title_short | Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research |
title_sort | utilising the intel realsense camera for measuring health outcomes in clinical research |
topic | Mobile & Wireless Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799357/ https://www.ncbi.nlm.nih.gov/pubmed/29404692 http://dx.doi.org/10.1007/s10916-018-0905-x |
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