Model Predictive Valve Control for Lung Pressure Profile Tracking Assistance
Over 12,000 people in the UK are diagnosed with a brain tumour every year. Current diagnostic methods are expensive and typically invasive, meaning that early, widespread screening is not possible. This paper develops a control set-up that enables a new, low-cost, non invasive eardrum sensor to provide accurate intracranial pressure measurements, thereby facilitating more effective diagnosis. The controller works by assisting participants to accurately track airway pressure profiles via blowing into a tube. This has the effect of removing blood flow fluctuations that would otherwise corrupt the eardrum sensor readings used to compute intracranial pressure.A new experimental hardware set-up, identification process and model predictive control approach are developed to compute the optimal sequence of valve positions, and experimental results show a 21% improvement in pressure profile tracking compared with existing clinical methods.
Authors
- M. C. Thompson (ORCID: https://orcid.org/0000-0002-3254-6804)
- Ann‐Marie Hughes (ORCID: https://orcid.org/0000-0002-3958-8206)
- R. Marchbanks
- Nicole O’Brien
- Christopher Freeman (ORCID: https://orcid.org/0000-0003-0305-9246)
- Anthony A. Birch (ORCID: https://orcid.org/0000-0002-2328-702X)
Institutions
- University Hospital Southampton NHS Foundation Trust (GB)
- University of Southampton (GB)
Publication Details
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1109/ccta60707.2024.10666580
- Primary Topic
- Hydraulic and Pneumatic Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00