Henry Glyde
Supporting self-management of COPD and asthma
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Supervisors:
Email: henry.glyde@bristol.ac.uk |
Project Summary:
The title of my research project is supporting self-management of COPD and asthma. The chief aim of the project is to develop models using Bayesian machine learning algorithms, run on my mhealth data that can predict an exacerbation of COPD or asthma days before its occurrence, enabling timely intervention. Other aims include combining the models with an early warning system for patients and clinicians who use my mhealth apps and identify if exacerbation frequency is reduced and to test the predictive ability of novel sensors (sleep sensors, cough detection frequency, e.t.c.)
General Profile:
I graduated from the University of Exeter with a 1st class BSc with honours in medical science. I have completed the taught year of my EPSRC Centre for Doctoral Training in Digital Health and Care.
Between September and March of 2018/19, I was characterising the pancreatic β-cell line (known as 1.2B4) to determine if it is suitable to study β-cell pathophysiology. My research was presented at the PEVNET consortium at Munich in 2019.
Between June and September of 2018, I worked on a project to design a three-dimensional shoulder. I received a small grant to segment a shoulder from a magnetic resonance image (MRI) using mimic innovation suite (MIS). This package is designed for computerised tomography (CT) scans, so I was tasked with devising a working method of applying MIS for MRI analysis. The 3D bio-realistic shoulder design will be used to test different prosthesis. The data produced will result in a paper that is to be published by the world council of biomechanics.I later presented a poster on my bio-realistic shoulder at the undergraduate medical school conference at the University of Exeter. I presented to students, members of the public, scientists, clinicians and surgeons.