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Real-time brain modelling for personalised neuro-therapeutic interventions in chronic pain

Real-time brain modelling for personalised neuro-therapeutic interventions in chronic pain 

Led by Dr Alex Casson, University of Manchester, in association with the University of Liverpool

Chronic pain is estimated to cost in excess of $600B per year in the US, together with considerable personal impacts on the individuals involved and their carers. This study aims to make new technological interventions for chronic pain, with a focus on fibromyalgia and osteoarthritis for which current treatment options (pharmaceuticals) are limited or associated with significant side effects. By employing technological factors such as electrical stimulation, tactile, sound or light stimulation we may create ‘electroceutical’ interventions which employ different pain relief mechanisms, with a different level of effectiveness, the project anticipates fewer side effects. In particular, this project seeks to create ‘closed loop’ devices where the stimulation parameters (such as frequency and phase) are automatically adjusted based upon currently sensed data in order to personalise the stimulation that is applied. To achieve this it will monitor brain activity (the EEG) to calculate the changes in the underlying brain networks which are being activated during an ‘electroceutical’ intervention, performing this ‘brain connectivity’ analysis in real-time. The proposal seeks to create new mathematical methods to allow this to be done on smartphone class hardware and to characterise the ‘speed’/latency required for creating closed loop devices.