PhD Studentship: Innovative Non-Invasive Microvascular Aassessment - Investigating the Relationship Between Patterns in Blood Flow and Oxygenation Signals

University of Southampton - Bioengineering, Faculty of Engineering and the Environment

A major challenge facing public health is the increased incidence and prevalence of cardio-metabolic and related diseases, e.g. diabetes and obesity. Changes in flowmotion, the spontaneous oscillation in tone of blood vessels, may precede other measures of autonomic dysfunction that occur in these diseases and could help in their early detection or treatment. Laser Doppler flowmetry provides a non-invasive technique for investigating the motion of haemoglobin and its oxygenated state allowing the assessment of microvascular function and possibly disease state. Similarly, near-infrared spectroscopy, can assess deep tissue oxygenation non-invasively, for example in the brain or muscle. Speckle imaging can be used to assess larger (~7cm x 7cm) areas of tissue giving spatial and temporal blood flow and oxygenation measurements.

This project is an innovative collaboration between scientists in Engineering and Medicine and leading medical instrument manufacturer Moor Instruments (www.moor.co.uk) to investigate the relationship between patterns in blood flow and oxygenation signals and their association with diseases and their progression. Computational techniques for time, frequency domain and complexity analysis will be developed and applied to data gathered from a wide set of volunteers using a variety of different stimuli. This may be complemented by the design of further volunteer-based studies to investigate more descriptive and discriminating challenges for data acquisition in particular disease cases.

This PhD offers a unique interdisciplinary programme of work within the Faculties of Engineering and the Environment and Medicine at the University of Southampton with the opportunity for placements at Moor Instruments. The PhD candidate will work closely with engineers, basic scientists and clinicians and may undertake physiological measurements on volunteers. It is an exciting opportunity for an ambitious and numerate graduate to develop interdisciplinary research skills applied to pressing health questions in our society.

The ideal candidate will have biomedical signal processing or time-series modelling experience and a good knowledge of computational analysis/modelling approaches. The candidate must have a strong background in engineering sciences and an enthusiasm to communicate across traditional discipline boundaries.

If you wish to discuss any details of the project informally, please contact Dr Andy Chipperfield, Bioengineering Science research group, Email: A.J.Chipperfield@soton.ac.uk, Tel: +44 (0) 2380 59 8344.

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Type / Role:

PhD

Location(s):

South East England