Breathing pattern disorder (BPD) results in breathlessness and distressing symptoms in the absence of, or in excess of, respiratory disease for which pharmacological management has been optimised. There is increasing awareness in respiratory medicine of BPD and reports on Long COVID cohorts have noted BPD prevalence. Surveys show many conditions, e.g., asthma, have symptoms that persist despite effective pharmacological management, affecting quality of life, and BPD is suggested as a contributory factor.
Assessment of BPD is currently solely via questionnaires or subjective assessment, affecting the specificity of intervention and meaning diagnosis is by exclusion of other conditions, prolonging time to diagnosis and effective treatment and reducing patient satisfaction. However, effective physiotherapy-led rehabilitation interventions exist for BPD, with GP practice surveys indicating that ~30-50% of patients experience reduction in symptoms following breathing pattern retraining.
Assessment of individual breathing patterns using 3D motion capture based technology (opto-electronic plethysmography – OEP) is an attractive candidate for respiratory assessment, diagnosis, and management, particularly for children, and for the evaluation of exercise-induced symptoms. It provides rich information about the contribution and timing of different chest wall sections during healthy and pathological breathing.
This project will build on previous work that has established OEP-based metrics to distinguish disordered breathing patterns from healthy breathing by extending these techniques to asthmatic breathing and Long Covid, and will assess whether real-time feedback on the breathing pattern can restore healthy breathing patterns in these groups to reduce symptoms. This project will lay the foundation for a simple breathing monitoring and retraining system derived from OEP methodology.
94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Primary supervisor: Dr Samantha L. Winter
The successful PhD candidate will demonstrate the necessary academic credentials and skills to be able cope with PhD level study. Whilst there will be strong leadership from the supervisory team, working on their own initiative is a required skill.
Applicants should have experience in respiratory physiology, or motion capture and be willing to learn the other discipline.
It is essential that applicants demonstrate some post-GCSE or high school mathematics experience. This could be via degree modules or other qualifications, a project or industrial experience, or other experience that should be detailed in the application. Some experience in working with data or statistical analysis is important.
Applicants must have a good Honours degree in an appropriate subject. Appropriate subjects are considered to be Sport and Exercise Science, Computing, Engineering, Physics, Mathematics or Statistics, biological or health sciences. A Master’s degree in a relevant subject is desirable.
More specific details about the project can be obtained by emailing S.L.Winter@kent.ac.uk.
Applicants must meet the minimum English language requirements. Further details are available on the International website.
All applications should be made online. Under programme name, select School of Sport, Exercise and Health Sciences. Please quote the advertised reference number: SSEHS/SLW24 in your application.
To avoid delays in processing your application, please ensure that you submit the minimum supporting documents, including a 2,000 word (maximum) research proposal should be included, that details: a clear statement of the problem, existing literature on the problem, appropriate research methods, scope and nature of the project, problems, challenges, issues and possible conclusions.
The following selection criteria will be used by academic schools to help them make a decision on your application.
To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (jobs-near-me.eu) you saw this job posting.
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