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Thesis
Home   /   Thesis   /   Adaptive neural decoder for a clinical ECoG-based Barin Computer Interface

Adaptive neural decoder for a clinical ECoG-based Barin Computer Interface

Abstract

CEA/LETI/CLINATEC invite applications for a PhD position financed by HORIZON-MSCA Doctoral Networks program. The aim of a networks research program is to leverage technical / therapeutic breakthroughs in the framework of multiple PhD projects that will continuously interact to converge toward effective combinatorial treatments/ function compensation for people with sever motor disabilities, e.g. due to a Spinal Cord Injury (SCI). In the frame of the training networks program, the goal of this PhD project will be to explore new solutions for functional rehabilitation and/or compensation using Brain-Machine Interfaces (BMI) / neuroprosthetics. Neuroprosthetics record, and decode brain neuronal signal to activate effectors (exoskeleton, implantable spinal cord stimulator etc.) directly, without the physiological neural control command interrupted by the SCI. A set of algorithms to decode neuronal activity recorded at the level of the cerebral cortex (Electrocorticogram) using chronic WIMAGINE implants were developed at CLINATEC and tested in the frame of 2 clinical research protocols: with tetraplegic patients in Grenoble and paraplegic patients in Lausanne. The PhD candidate will contribute to the next highly ambitious scientific breakthrough addressing the medical needs of efficient, unassisted and easy-to-use embedded neuroprosthetics. Innovative adaptive BMI will be explored, tested offline and in real-time in the ongoing clinical trials. CLINATEC is looking for a candidate, specialized in the fields of machine learning, and neural signal processing.

Laboratory

Clinatec (LETI)
Clinatec (LETI)
Clinatec (LETI)
Université Grenoble Alpes
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