IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2004 · 276 citations · 11 references
EngineeringComputer ScienceNeuroscienceElectrophysiologyMotor ControlNeural EngineeringBrain-computer InterfacesContinuous ElectroencephalographyElectroencephalogram AnalysisElectroencephalogram Signal ProcessingElectroencephalographyMental ImageryBrain-computer Interface ClassificationClassification Algorithms For Brain-computer InterfacesElectroencephalogram ClassificationElectroencephalographic Pattern ClassificationElectroencephalography-based Brain-computer InterfacesMotor Imagery ClassificationResting-state EegTime Windows
Nearly all electroencephalogram (EEG)-based brain-computer interface (BCI) systems operate in a cue-paced or synchronous mode. This means that the onset of mental activity (thought) is externally-paced and the EEG has to be analyzed in predefined time windows. In the near future, BCI systems that allow the user to intend a specific mental pattern whenever she/he wishes to produce such patterns will also become important. An asynchronous BCI is characterized by continuous analyzing and classification of EEG data. Therefore, it is important to maximize the hits (true positive rate) during an intended mental task and to minimize the false positive detections in the resting or idling state. EEG data recorded during right/left motor imagery is used to simulate an asynchronous BCI. To optimize the classification results, a refractory period and a dwell time are introduced.
11
Pattern Classification and Scene Analysis
Michael Thompson, Richard O. Duda, Peter E. Hart · Leonardo · 1974 · 4.5K citations
Motor imagery and direct brain-computer communication
G. Pfurtscheller, Christa Neuper · Proceedings of the IEEE · 2001 · 1.9K citations