Tremor is the most common movement disorder and it is strongly increasing in incidence and prevalence with ageing. More than 65% of the population with upper limb tremor presents serious difficulties in performing activities of daily living (ADL). Tremor is not life-threatening, but it can be responsible for functional disability and social inconvenience. It is typically managed by means of drugs, surgery (thalamotomy), and deep brain stimulation, but treatments are not effective in approximately 25% of patients.The main objective of the project is to validate, technically, functionally and clinically, the concept of mechanically suppressing tremor through selective Functional Electrical Stimulation (FES) based on a (Brain-to-Computer Interaction) BCI-driven detection of involuntary (tremor) motor activity:- The system will detect and monitor involuntary motor activity (tremor) through a multimodal BCI. The proposed BCI will combine CNS (Electroencephalography, EEG) and PNS (Electromyography, EMG) data with biomechanical data (Inertial Measurement Units, IMUs) in a sensor fusion approach. It will model and track tremor and voluntary motion.- It will also include a multi-channel array FES system for selective stimulation of muscles for tremor suppression while reducing the influence on voluntary motion.- For a potential commercial exploitation the embodiment must fit potential user expectations in terms of cosmetics, functionality and aesthetics.TREMOR proposes a multimodal BCI in which the main goal is identifying, characterizing and tracking involuntary motor bioelectrical activity as a command to trigger a biomechanical suppression of tremor.