Exoskeletal robots (ERs) are person-oriented robots that supplement the function of a limb or replace it completely. A possible alternative to ERs are Motor Neuro-Prostheses (MNP) based on Functional Electrical Stimulation (FES). Both ERs and MNPs are technologies that seek to restore or substitute motor function. MNPs constitute an approach to restoring function by means of artificially controlling human muscles or muscle nerves with FES. ERs use volitional commands for controlling the application of controlled forces to drive paralyzed or weak limbs.

The main goal of BRAIN2MOTION project is to develop a new hybrid ER-MNP for the upper limb interfaced to the users by means of non-invasive multimodal brain-neural computer interfaces (BNCIs). The robotic hybrid system will combine a light and kinematically compatible ER, and a textile-based surface MNP. In this combined ER-MNP, hardware and control strategies will be developed to combine the action of the ER and MNP while preserving motor latent capabilities of the user. A spontaneous non- invasive EEG-based Brain-Computer Interface (BCI) and an electrooculography (EOG) interface will compose the multimodal BNCI. The BCI will differentiate more than three mental tasks. This will be achieved incorporating new adaptive classifiers into the BCI. Learning strategies will be developed in order to improve the performance and versatility of the BCI. Control strategies combining EEG and EOG signals will be developed to control the ER-MNP.

The hybrid ER-MNP controlled by the BNCI will be used to perform reaching and grasping operations. The system will be validated with patients suffering from neurological conditions leading to severe motor disorders, in particular cerebrovascular accident (CVA).