Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …

Background Hand rehabilitation is core to helping stroke survivors regain activities of daily
living. Recent studies have suggested that the use of electroencephalography-based brain …

Objective Chronic stroke patients with severe hand weakness respond poorly to
rehabilitation efforts. Here, we evaluated efficacy of daily brain–machine interface (BMI) …

Electroencephalography (EEG)–based motor imagery (MI) brain-computer interface (BCI)
technology has the potential to restore motor function by inducing activity-dependent brain …

The recovery of hand function is one of the most challenging topics in stroke rehabilitation.
Although the robot‐assisted therapy has got some good results in the latest decades, the …

While recent research on Brain-Computer Interfaces (BCI) has highlighted their potential for
many applications, they remain barely used outside laboratories. The main reason is their …

Electroencephalography (EEG) signals have great impact on the development of assistive
rehabilitation devices. These signals are used as a popular tool to investigate the functions …

After an initial period of recovery, human neurological injury has long been thought to be
static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or …

In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI)
based Brain Computer Interfaces (BCIs) called EEGSym. Our implementation aims to …

BACKGROUND: Motor paralysis after stroke has devastating consequences for the patients,
families and caregivers. Although therapies have improved in the recent years, traditional …