About the project
Blood flow to the brain is controlled by a series of interacting complex physiological mechanisms that ensure an adequate supply at all times. Of particular interest in this project is the control of flow in response to changes in blood pressure, generally known as ‘cerebral autoregulation’, whose dysfunction has been associated with many clinical conditions, from prematurity in babies to dementia, head-trauma and stroke.
Knowledge of patients' autoregulatory impairment is expected to guide the management of their blood pressure in the clinic, especially in intensive care. Methods to assess autoregulation in patients still present many challenges, and usually involve simultaneous monitoring of blood flow (from Doppler ultrasound measurement) and blood pressure, as well as other physiological variables, such as gas concentrations in exhaled air.
Mathematical modelling of the interaction between these signals can then provide measures of regulatory activity. Most research in this field has focused on time-invariant models, but there is strong evidence that this is inadequate. Changes in the strength of blood flow control over time may be occurring spontaneous or in response to the size of blood pressure fluctuations, or other factors. Neglecting this variability will degrade the assessment of patients' cerebral blood supply and hence their clinical management.
In the current project we will develop, test and optimise signal analysis methods to tackle this time-varying and signal dependent behaviour of blood flow control. The methods will be applied to data collected in previous research studies. The aims are to improve understanding of the physiological control system and identify markers of function/impairment that can be used in clinical practice.
Successful candidates will have a strong background in signal processing, and previous experience with biomedical applications will be advantageous. The project will be carried out in collaboration with partners at the Universities of Leicester and Cambridge.
We are seeking PhD students who have a background in signal processing, biomedical engineering or related fields. A desire to work at the forefront of the interface between engineering, physiology and clinical medicine is a requirement. The main research activity will be in the development, implementation, testing and optimization of signal analysis methods.
