The brain–computer interface (BCI) is an emerging technology that has the potential to
revolutionize the world, with numerous applications ranging from healthcare to human …

Stroke is one of the leading causes of long-term disability among adults and contributes to
major socio-economic burden globally. Stroke frequently results in multifaceted impairments …

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 …

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized
computer vision through end‐to‐end learning, that is, learning from the raw data. There is …

Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals
into intended movements of the paralyzed limb. However, the efficacy and mechanisms of …

Neurofeedback is a psychophysiological procedure in which online feedback of neural
activation is provided to the participant for the purpose of self-regulation. Learning control …

Brain–computer interfaces (BCIs) use brain activity to control external devices, thereby
enabling severely disabled patients to interact with the environment. A variety of invasive …

Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from
neurophysiology, computer science, and engineering in an effort to establish real-time …

Brain‐computer interfaces (BCI s) can provide sensory feedback of ongoing brain
oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully …

Background A substantial number of clinical studies have demonstrated the functional
recovery induced by the use of brain-computer interface (BCI) technology in patients after …