Improving the separability of motor imagery EEG signals using a cross correlation-based least square support vector machine for brain-computer interface

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 20, Issue 4, 2012, Pages 526-538

  Siuly, Siuly ^a   Li, Yan ^a  

^a UNIVERSITY OF SOUTHERN QUEENSLAND   (Australia)

Author keywords

Brain computer interface (BCI); cross correlation technique; electroencephalogram (EEG); feature extraction; kernel logistic regression; least square support vector machine (LS SVM); logistic regression; motor imagery (MI)

Indexed keywords

BRAIN-COMPUTER INTERFACES (BCI); CROSS CORRELATION TECHNIQUES; KERNEL LOGISTIC REGRESSION; LEAST SQUARE SUPPORT VECTOR MACHINES; LOGISTIC REGRESSIONS; MOTOR IMAGERY;

ALGORITHMS; CORRELATION METHODS; ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; LOGISTICS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

BRAIN COMPUTER INTERFACE;

ADULT; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER INTERFACE; COMPUTER SIMULATION; EVOKED MUSCLE RESPONSE; FEMALE; HUMAN; IMAGINATION; MALE; METHODOLOGY; MOTOR CORTEX; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; PSYCHOPHYSIOLOGY; REGRESSION ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICS; SUPPORT VECTOR MACHINE;

BIOFEEDBACK, PSYCHOLOGY; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; EVOKED POTENTIALS, MOTOR; FEMALE; HUMANS; IMAGINATION; LEAST-SQUARES ANALYSIS; MALE; MODELS, NEUROLOGICAL; MOTOR CORTEX; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STATISTICS AS TOPIC; SUPPORT VECTOR MACHINES; USER-COMPUTER INTERFACE; YOUNG ADULT;

EID: 84863763866     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2012.2184838     Document Type: Article

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