2013 · 13 citations · 53 references
EngineeringNeurologyNeuroscienceNeural EngineeringNeurorehabilitationRehabilitationBrain-computer InterfacesElectroencephalogram AnalysisElectroencephalogram Signal ProcessingElectroencephalographyNeurological RehabilitationBrain-computer Interface RehabilitationBrain-computer Interface Signal AcquisitionBrain-computer Interface Signal AnalysisBrain-computer Interface Signal ProcessingBrain-machine InterfacesBrainstem StrokeElectroencephalography-based Brain-computer InterfacesPost-stroke Communication Therapy
Abstract: Several patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us do it. For instance, severe cases astetraplegic or post-stroke patients are literally 'locked in ' their bodies, unable to exert any motor control after a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. However, in the near future, their brains may offer them a way out. EEG-based braincomputer interface (BCI) is the technique utilized to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a spelling system via eye movements). Here,we aim to review the basic concepts of EEG-based BCI and the main advances in communication, in motor control restoration and in downregulation of cortical activitythat seem to be relevant for clinical applications in the coming years forneurorehabilitation of severely limited patients. It allows brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. In addition, epilepsy and attention deficit and hyperactive disorder patients were able to downregulate their cortical activity. Owing to the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas related to clinical neurorehabilitation of severely limited
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Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks
G. Pfurtscheller, Clemens Brunner, Alois Schlögl et al. · NeuroImage · 2006 · 1.6K citations
Medicine, Neurobiology, Neuroscience +16