IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2006 · 239 citations · 17 references
EngineeringNeuroscienceElectrophysiologyMotor ControlNeural EngineeringBrain-computer InterfacesElectroencephalogram AnalysisElectroencephalogram Signal ProcessingElectroencephalographyEvoked PotentialsNeural InterfacesBrain-computer Interface Performance EvaluationBrain-computer Interface Signal AcquisitionBrain-computer Interface Signal AnalysisBrain-computer Interface Signal ProcessingElectrocorticography-based Brain-computer InterfacesElectrocorticography-based ControlElectroencephalography-based Brain-computer InterfacesFeedback
Electrocorticography (ECoG) has been demonstrated to be an effective modality as a platform for brain-computer interfaces (BCIs). Through our experience with ten subjects, we further demonstrate evidence to support the power and flexibility of this signal for BCI usage. In a subset of four patients, closed-loop BCI experiments were attempted with the patient receiving online feedback that consisted of one-dimensional cursor movement controlled by ECoG features that had shown correlation with various real and imagined motor and speech tasks. All four achieved control, with final target accuracies between 73%-100%. We assess the methods for achieving control and the manner in which enhancing online control can be accomplished by rescreening during online tasks. Additionally, we assess the relevant issues of the current experimental paradigm in light of their clinical constraints.
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Neuronal Population Coding of Movement Direction
Apostolos P. Georgopoulos, Andrew B. Schwartz, Ronald E. Kettner · Science · 1986 · 3.2K citations
Direct Cortical Control of 3D Neuroprosthetic Devices
Dawn M. Taylor, Stephen I. Helms Tillery, Andrew B. Schwartz · Science · 2002 · 1.6K citations