A 3D machine vision method for non-invasive assessment of respiratory function

Smith, L. N.; Smith, M. L.; Fletcher, M. E.; Henderson, A. J.

Abstract

Copyright © 2015 John Wiley & Sons, Ltd. Background: Respiratory function testing is important for detecting and monitoring illness, however, it is difficult for some patients, such as the young and severely ill, to perform conventional tests that require cooperation and/or patient contact. Method: A new method was developed for non-contact breathing measurement, employing photometric stereo to capture the surface topography of the torso of an unconstrained subject. The surface is integrated to calculate time-dependent volume changes during respiration. Results: The method provides a useful means of continuously measuring volume changes during respiration with high spatial and temporal resolution. The system was tested by comparison with pneumotachometry equipment and a clear periodic signal, of a frequency corresponding to the reference data, was observed. Conclusion: The approach is unique in performing breathing monitoring (with potential diagnostic capability) for unconstrained patients in virtually any lighting conditions (including darkness during sleep) and in a non-contact, unobtrusive (i.e. using imperceptible light) fashion. Copyright © 2015 John Wiley & Sons, Ltd.

• Journal Article Type: Article
• Acceptance Date: Apr 12, 2015
• Online Publication Date: May 13, 2015
• Publication Date: Jun 1, 2016
• Deposit Date: May 18, 2015
• Publicly Available Date: May 13, 2016
• Journal: International Journal of Medical Robotics and Computer Assisted Surgery
• Print ISSN: 1478-5951
• Electronic ISSN: 1478-596X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 2
• Pages: 179-188
• DOI: https://doi.org/10.1002/rcs.1669
• Keywords: respiratory function tests, critical care, 3D machine vision
• Public URL: https://uwe-repository.worktribe.com/output/912014
• Publisher URL: http://dx.doi.org/10.1002/rcs.1669
• Additional Information: Additional Information : This is the peer reviewed version of the following article: Smith, L., Smith, M. L., Fletcher, M. and Henderson, A. J. (2015) A 3D machine vision method for non-invasive assessment of respiratory function. International Journal of Medical Robotics and Computer Assisted Surgery. ISSN 1478-5951, which has been published in final form at http://dx.doi.org/10.1002/rcs.1669. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
• Contract Date: Apr 23, 2016