2011 · 54 citations · 8 references
EngineeringMeasurementBiometricsDetection TechniqueSocial SciencesBrain Computer InterfaceStatistical Signal ProcessingData SciencePattern RecognitionNeurologyIndependent Component AnalysisSignal DetectionSensor Signal ProcessingCanonical Correlation AnalysisComputer EngineeringNeuroimagingMinimum Energy CombinationSignal ProcessingNeural InterfaceBrain-computer InterfaceNeurophysiologyComputational NeuroscienceEeg Signal ProcessingNeuroscienceBraincomputer InterfaceSsvep Detection
Minimum energy combination (MEC) and canonical correlation analysis (CCA) are widely used for steady-state visual evoked potential (SSVEP) based brain computer interface (BCI), since both approaches have satisfactory performance. The purpose of this paper is to provide a guideline on choice of detection method, through comparison of the performance of the two approaches from simulation data and real SSVEP data. The experiment results show that CCA has lower deviation, higher accuracy and higher signal to noise ratio than MEC.
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A practical VEP-based brain-computer interface
Yijun Wang, Ruiping Wang, Xiaorong Gao et al. · IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2006 · 610 citations