Adaptive BCI Based on Variational Bayesian Kalman Filtering: An Empirical Evaluation

IEEE Transactions on Biomedical Engineering

Volumn 51, Issue 5, 2004, Pages 719-727

  Sykacek, Peter ^a   Roberts, Stephen J ^a   Stokes, Maria ^b  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b ROYAL LONDON HOSPITAL   (United Kingdom)

Author keywords

Adaptive classification; Bayesian learning; BCI; Variational method

Indexed keywords

ADAPTIVE ALGORITHMS; BRAIN; COGNITIVE SYSTEMS; ELECTROENCEPHALOGRAPHY; KALMAN FILTERING; PROBABILITY; VARIATIONAL TECHNIQUES;

BRAIN COMPUTER INTERFACE; GENERALIZATION; LEARNING EFFECTS; ROBUSTNESS;

BIOMEDICAL ENGINEERING;

ACCURACY; ALGORITHM; ARTICLE; BAYES THEOREM; COGNITION; DATA ANALYSIS; ELECTRODE; ELECTROENCEPHALOGRAM; EMPIRICISM;

ALGORITHMS; BAYES THEOREM; BRAIN; COGNITION; COMMUNICATION AIDS FOR DISABLED; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; FEEDBACK; HUMANS; MODELS, ANATOMIC; MODELS, STATISTICAL; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES; SYSTEMS THEORY; USER-COMPUTER INTERFACE;

EID: 1942489160     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2004.824128     Document Type: Article

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