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Development of a smart-fit system for CPAP interface selection
Continuous Positive Airway Pressure (CPAP) therapy is commonly prescribed for longstanding, acute cases of Obstructive Sleep Apnea (OSA) during which patients must wear a tight-fitting breathing mask overnight for the duration of the treatment. Because this condition frequently leads to the permanen...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780270/ https://www.ncbi.nlm.nih.gov/pubmed/32988316 http://dx.doi.org/10.1177/0954411920959879 |
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author | Ma, Zhichao Hyde, Philip Drinnan, Michael Munguia, Javier |
author_facet | Ma, Zhichao Hyde, Philip Drinnan, Michael Munguia, Javier |
author_sort | Ma, Zhichao |
collection | PubMed |
description | Continuous Positive Airway Pressure (CPAP) therapy is commonly prescribed for longstanding, acute cases of Obstructive Sleep Apnea (OSA) during which patients must wear a tight-fitting breathing mask overnight for the duration of the treatment. Because this condition frequently leads to the permanent use of CPAP masks, interface selection is a crucial factor influencing the treatment quality and effectiveness. Masks/interface selection is normally performed on a trial an error basis with clinicians informing their selection based on OSA-related factors with basic fitting feedback from patients. However, it is not uncommon for patients to abandon the treatment or request additional consultations due to ill-fitting CPAP mask with the main sources of discomfort being perceived air leakage and mask/strap overtightening leading to skin damage. This work introduces a novel system (Smart-Fit), for CPAP interface selection using advanced digital technologies, such as Reverse Engineering and Computational Modeling (Finite Element Analysis) which are paired to evaluate and determine the best fitting interface for each clinical case. The model simplifies the number of 3D facial landmarks to 12 and established that a 2 mm scan resolution is enough for accurate scans. The Von Mises stress map in ANSYS serves as an indicator of potential high-pressure areas, triggering the need for a chance of mask size. Current results indicate the Smart Fit System can enable a “best fit CPAP interface” to be selected considering individual’s physical characteristics and existing CPAP interface configurations. The development of the Smart Fit System is an evolution compared to traditional CPAP interface selection approach, which optimizes the CPAP interface selection process. |
format | Online Article Text |
id | pubmed-7780270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-77802702021-01-13 Development of a smart-fit system for CPAP interface selection Ma, Zhichao Hyde, Philip Drinnan, Michael Munguia, Javier Proc Inst Mech Eng H Original Articles Continuous Positive Airway Pressure (CPAP) therapy is commonly prescribed for longstanding, acute cases of Obstructive Sleep Apnea (OSA) during which patients must wear a tight-fitting breathing mask overnight for the duration of the treatment. Because this condition frequently leads to the permanent use of CPAP masks, interface selection is a crucial factor influencing the treatment quality and effectiveness. Masks/interface selection is normally performed on a trial an error basis with clinicians informing their selection based on OSA-related factors with basic fitting feedback from patients. However, it is not uncommon for patients to abandon the treatment or request additional consultations due to ill-fitting CPAP mask with the main sources of discomfort being perceived air leakage and mask/strap overtightening leading to skin damage. This work introduces a novel system (Smart-Fit), for CPAP interface selection using advanced digital technologies, such as Reverse Engineering and Computational Modeling (Finite Element Analysis) which are paired to evaluate and determine the best fitting interface for each clinical case. The model simplifies the number of 3D facial landmarks to 12 and established that a 2 mm scan resolution is enough for accurate scans. The Von Mises stress map in ANSYS serves as an indicator of potential high-pressure areas, triggering the need for a chance of mask size. Current results indicate the Smart Fit System can enable a “best fit CPAP interface” to be selected considering individual’s physical characteristics and existing CPAP interface configurations. The development of the Smart Fit System is an evolution compared to traditional CPAP interface selection approach, which optimizes the CPAP interface selection process. SAGE Publications 2020-09-28 2021-01 /pmc/articles/PMC7780270/ /pubmed/32988316 http://dx.doi.org/10.1177/0954411920959879 Text en © IMechE 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Articles Ma, Zhichao Hyde, Philip Drinnan, Michael Munguia, Javier Development of a smart-fit system for CPAP interface selection |
title | Development of a smart-fit system for CPAP interface
selection |
title_full | Development of a smart-fit system for CPAP interface
selection |
title_fullStr | Development of a smart-fit system for CPAP interface
selection |
title_full_unstemmed | Development of a smart-fit system for CPAP interface
selection |
title_short | Development of a smart-fit system for CPAP interface
selection |
title_sort | development of a smart-fit system for cpap interface
selection |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780270/ https://www.ncbi.nlm.nih.gov/pubmed/32988316 http://dx.doi.org/10.1177/0954411920959879 |
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