In this study, we propose a graph sequence neural network (GSNN) to accurately decode patterns of motor imagery from electroencephalograms (EEGs) in the presence of distractions. GSNN aims to build ...

In this paper, an asynchronous control paradigm based on sequential motor imagery (sMI) is proposed to enrich the control commands of a motor imagery -based brain-computer interface. We test the ...

Abstract Activities of daily living rely on our ability to acquire new motor skills composed of precise action sequences. Early learning of a new sequential skill is characterized by steep performance ...