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746,000 people currently live with Spinal Cord Injury (SCI) in EU and in the US, with approximately 31,000 new cases in EU and 18,000 in the US each year, with dramatic human, societal and economical costs. SCI leads to severe neurological deficits. Locomotion impairment or the loss of upper limb functions requires caregivers and dramatically impacts autonomy in every day life.
Currently, there is no approved therapy to improve motor recovery from SCIs.
Motor Brain Machine Interfaces (BMIs) aim at translating brain neural signals into commands to external
 or internal
 effectors using e.g. electrical stimulation of the spinal cord. In addition, as demonstrated in non-human primates, brain-controlled spinal cord stimulation may allow natural neuroprosthetic control and restore voluntary movements . Short-term BMI proof-of-concepts
,  were milestones, but had the major limitation of using transcutaneous connectors. The ongoing clinical trials carried out by EPFL and CEA (STIMO-BSI - NCT04632290, and ‘BCI&Tetraplegia’ - NCT02550522) raise great hopes for SCI patients, effectively assessing the feasibility of chronic Electrocorticography (ECoG)-based motor BMI . Wireless ECoG recording systems used in these clinical trials are far more appropriate for long-term application or during rehabilitation period. At the same time, these clinical trials highlight essential barriers to bring Motor BMI to clinical practice. Indeed, brain activity decoding to supply motor functions supposes a model in the decoding software, which requires a calibration.
The necessity of regular decoder retraining from neural activity recording, in a supervised manner and in well-controlled environments, is one of the major barriers for long-term use of BMI at home. In addition, due to their novelty, BMI systems are still an assembly of separate components including recording hardware (brain signals filtering / amplification / digitalization), data streaming and remote power supply hardware, dedicated computer with software to decode the digitalized brain signals and controlling the effectors. BMI systems are cumbersome, complicated to install, and often require a team of engineers to operate them
This project aims at achieving 3 major methodological and technological breakthroughs toward assistance-free and easy to use portable neuroprosthetics with BMI signal processing integrated technology in medical practice (Fig. 1). The intended breakthroughs are:
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.