[Eeglablist] PhD scholarship Machine learning and pain

[Aleksandra Vuckovic]

Hi

Rehabilitation Engineering group at the School of Engineering, University of Glasgow is looking for applicants for 3.5 years funded project “Electroencephalograph predictors of central neuropathic pain in subacute spinal cord injury”

Project abstract:

Central neuropathic pain (CNP) affects 7% of the general population and more than 50% of people with spinal cord injury (SCI). We propose to define how EEG markers of CNP evolve over time in SCI, starting before the onset of its physical symptoms. Early EEG markers will be used to identify the risk of each newly injured patient developing pain to recommend preventive treatment. The PI team have recently shown that multichannel EEG classification can predict the risk of pain with an average accuracy of 86% (https://www.ncbi.nlm.nih.gov/pubmed/29886266).

In this project we propose to validate the EEG classifier and to optimize its performance.  The ultimate goal is to have a pain predictor based on a minimum number of EEG channels from key areas. In addition, a longitudinal study will reveal how spontaneous and evoked EEG markers evolve during the transition from subacute to chronic SCI CNP, improving our understanding of mechanisms.



Interested applications should contact:



Dr Aleksandra Vuckovic, PhD Biomed Eng

Senior Lecturer in Rehabilitation Engineering

School of Engineering

http://www.gla.ac.uk/schools/engineering/staff/aleksandravuckovic/