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Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system
Respiratory disease is the leading cause of death in the UK. Methods for assessing pulmonary function and chest wall movement are essential for accurate diagnosis, as well as monitoring response to treatment, operative procedures and rehabilitation. Despite this, there is a lack of low-cost devices...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069336/ https://www.ncbi.nlm.nih.gov/pubmed/26872677 http://dx.doi.org/10.1007/s11517-015-1433-1 |
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author | Harte, James M. Golby, Christopher K. Acosta, Johanna Nash, Edward F. Kiraci, Ercihan Williams, Mark A. Arvanitis, Theodoros N. Naidu, Babu |
author_facet | Harte, James M. Golby, Christopher K. Acosta, Johanna Nash, Edward F. Kiraci, Ercihan Williams, Mark A. Arvanitis, Theodoros N. Naidu, Babu |
author_sort | Harte, James M. |
collection | PubMed |
description | Respiratory disease is the leading cause of death in the UK. Methods for assessing pulmonary function and chest wall movement are essential for accurate diagnosis, as well as monitoring response to treatment, operative procedures and rehabilitation. Despite this, there is a lack of low-cost devices for rapid assessment. Spirometry is used to measure air flow expired, but cannot infer or directly measure full chest wall motion. This paper presents the development of a low-cost chest wall motion assessment system. The prototype was developed using four Microsoft Kinect sensors to create a 3D time-varying representation of a patient’s torso. An evaluation of the system in two phases is also presented. Initially, static volume of a resuscitation mannequin with that of a Nikon laser scanner is performed. This showed the system has slight underprediction of 0.441 %. Next, a dynamic analysis through the comparison of results from the prototype and a spirometer in nine cystic fibrosis patients and thirteen healthy subjects was performed. This showed an agreement with correlation coefficients above 0.8656 in all participants. The system shows promise as a method for assessing respiratory disease in a cost-effective and timely manner. Further work must now be performed to develop the prototype and provide further evaluations. |
format | Online Article Text |
id | pubmed-5069336 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-50693362016-11-02 Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system Harte, James M. Golby, Christopher K. Acosta, Johanna Nash, Edward F. Kiraci, Ercihan Williams, Mark A. Arvanitis, Theodoros N. Naidu, Babu Med Biol Eng Comput Original Article Respiratory disease is the leading cause of death in the UK. Methods for assessing pulmonary function and chest wall movement are essential for accurate diagnosis, as well as monitoring response to treatment, operative procedures and rehabilitation. Despite this, there is a lack of low-cost devices for rapid assessment. Spirometry is used to measure air flow expired, but cannot infer or directly measure full chest wall motion. This paper presents the development of a low-cost chest wall motion assessment system. The prototype was developed using four Microsoft Kinect sensors to create a 3D time-varying representation of a patient’s torso. An evaluation of the system in two phases is also presented. Initially, static volume of a resuscitation mannequin with that of a Nikon laser scanner is performed. This showed the system has slight underprediction of 0.441 %. Next, a dynamic analysis through the comparison of results from the prototype and a spirometer in nine cystic fibrosis patients and thirteen healthy subjects was performed. This showed an agreement with correlation coefficients above 0.8656 in all participants. The system shows promise as a method for assessing respiratory disease in a cost-effective and timely manner. Further work must now be performed to develop the prototype and provide further evaluations. Springer Berlin Heidelberg 2016-02-13 2016 /pmc/articles/PMC5069336/ /pubmed/26872677 http://dx.doi.org/10.1007/s11517-015-1433-1 Text en © The Author(s) 2016 Open AccessThis 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 | Original Article Harte, James M. Golby, Christopher K. Acosta, Johanna Nash, Edward F. Kiraci, Ercihan Williams, Mark A. Arvanitis, Theodoros N. Naidu, Babu Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title | Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title_full | Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title_fullStr | Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title_full_unstemmed | Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title_short | Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect-based motion tracking system |
title_sort | chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel kinect-based motion tracking system |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069336/ https://www.ncbi.nlm.nih.gov/pubmed/26872677 http://dx.doi.org/10.1007/s11517-015-1433-1 |
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