Non-invasive Brain-computer-interfaces for Remote Rehab and Training of Motor Skills​ 

Investigators:

  • Katja Kornysheva (University of Birmingham)
  • Anna Sadnicka (UCL)
  • Dr Fei He (Coventry University)
  • Atif Shahzad (University of Birmingham)
  • Amin Rahmat (University of Birmingham)
  • Drummond Masterdon (Falmouth University)

 

Funded: £34,464.65 over 12 months.

In the UK, 1.3 million stroke survivors and 145,000 Parkinson’s Disease (PD) patients encounter movement problems, hindering work and independence, costing around £42 billion a year. Current state-of-the-art rehabilitation fails to reach all patients and we need methods in which the dose of therapy can be increased without requiring an increase in resources.  

While invasive brain-computer-interfaces (BCIs) have been used for prosthetic control, closed-loop brain stimulation, and neurofeedback, they come with multiple health risks and costs with only a small proportion of patients being eligible. In contrast, current non-invasive brain recording technology, such as functional infrared spectroscopy (fNIRS) and EEG, have so far focussed on decoding simple movements rather than more complex naturalistic action sequences and their associated neuronal activity. In this high-risk-high-gain seed project, we aim to address three key translational research questions: 

  1. How can we provide individuals with access to their internal brain states associated with action planning in real-time? 
  2. Which neurofeedback protocol is suitable to enable individuals to control these states?
  3. Will achieving target brain states during action planning improve subsequent action execution? 

 

The project aims to deliver the groundwork towards a first prototype of a portable EEG neurofeedback application that allows a participant to monitor and learn to control their hidden neural action planning activity in real-time in order to optimise action performance. The readout and feedback on the internal action-related electrophysiological patterns may facilitate innovative neurotechnological advances for remote rehabilitation of patients with impairment of manual coordination to train beneficial preparatory patterns prior to initiating an action and help provide remote, individualised, patient-centred training. 

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