Detection of dysfunctional breathing using structured light plethysmography

Alhuthail, Eyas Ahmed ORCID: 0000-0001-6360-0650 (2023). Detection of dysfunctional breathing using structured light plethysmography. University of Birmingham. Ph.D.

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Abstract

Dysfunctional breathing (DB) is a term often used to describe irregularities of breathing in patients. In practice, the detection of DB is primarily subjective in nature with a focus on questionnaires and physical examination that can be influenced by personal judgment. Development of new techniques and approaches to allow quantification of DB is required. This thesis introduced the use Structured Light Plethysmography (SLP) in the detection of dysfunctional breathing and exploring the variability that exists in normal breathing patterns. SLP provides the assessment of tidal breathing pattern measures while allowing measurements to be made in different positions due to it being mobile and flexible. In the first study, SLP demonstrated reproducible results when repeated on different occasions. DB patterns present with changes in breathing patterns and SLP correlated well with these, albeit some differences in rapid shallow breathing. The second study focused on the development of an entropy measurement that quantifies the variability in breathing pattern. Patients with a restrictive condition showed a more controlled breathing pattern, whereas in obstructive patients the entropy varied with body position. The last study was focused on the assessment of changes in breathing patterns of post-COVID-19 patients from ward and ITU units compared to healthy subjects, this has shown a persistent mild restrictive pattern approximately 3 months after discharge without a significant change in the entropy of breathing suggesting some long term effects of hospitalisation due to COVID-19. The overall outcome allow for the use of SLP in different positions and demonstrated the ability to detect different breathing patterns and suitability of entropy analysis to be applied to the data acquired showing another measure of variability. With further investigation, analysis of the variability of breathing patterns may be an additional tool to help understand DB.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):