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Prediction of motor performance of patients with Parkinson's disease

Signal processing and machine learning on brain data.

Deep brain stimulation (DBS) is a standard clinical treatment for advanced stages of Parkinson's Disease (PD). Together with clinical partners, we have developed an experimental paradigm that allows to measure hand motor performance and brain signals simultaneously, while undergoing DBS therapy. This is the data you will be working with.

Project task: identify neural signal features from the electroencephalogram or invasive recordings, which are informative about the motor performance of patients with PD. Improve existing classification / regression methods for these neural features.

Skills required

  • Machine learning background
  • Good programming skills in python (familiarity numpy, sklearn are a plus).
  • Good mathematical background and intuition.
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