LFP

Electric and magnetic brain signals recordings (M/EEG, sEEG, LFP) are prone to a contamination by so-called artifacts, which do not have a neural origin but are caused by sensor problems, external electro-magnetic sources, or by bio-signals such as muscle activity.

Context For the rehabilitation training after stroke, simple repetitive hand motor tasks have been developed. One of them, the Sequential Visual Isometric Pinch Task (SVIPT) has been performed in studies with healthy users and stroke patients while the user’s brain activity (electroencephalogram, EEG) has been recorded.

Context Simple repetitive hand motor tasks, such as those used for rehabilitation training after stroke, are known to show strong trial-by-trial performance variations even though a trial typically lasts a few seconds only.

Context While deep learning approaches have significantly pushed language applications like keyword spotting in audio recordings, natural language processing on text documents etc., these solutions for the masses can not applied directly to non-standard speech signals, e.

Context Reinforcement learning (RL) methods interact with a system in closed loop in order to learn suitable action strategies. The goal of this interaction is to control the system, e.g., to bring it into a desired state.