Weighted spatial based geometric scheme as an efficient algorithm for analyzing single-trial EEGS to improve cue-based BCI classification

Neural Networks

Volumn 92, Issue , 2017, Pages 69-76

  Alimardani, Fatemeh ^a,b   Boostani, Reza ^a,d   Blankertz, Benjamin ^c  

^a SHIRAZ UNIVERSITY   (Iran)

^b INSTITUTE FOR ADVANCED STUDIES IN BASIC SCIENCES IASBS   (Iran)

^c TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

^d School of Electrical and Computer Engineering   (Iran)

Author keywords

Covariance matrix; Cue based Brain computer interface; Riemannian geometry; Weighting algorithm

Indexed keywords

COVARIANCE MATRIX; ELECTROENCEPHALOGRAPHY; GEOMETRY; INTERFACES (COMPUTER); VECTOR SPACES;

COMMON SPATIAL PATTERNS; EEG SIGNALS; ELECTRO-ENCEPHALOGRAM (EEG); MENTAL TASKS; RIEMANNIAN FRAMEWORK; RIEMANNIAN GEOMETRY; SINGLE TRIAL; WEIGHTING SCHEME;

BRAIN COMPUTER INTERFACE;

ACCURACY; ALGORITHM; ARTICLE; ASSOCIATION; BRAIN COMPUTER INTERFACE; CLASSIFICATION; CONCEPTUAL FRAMEWORK; DATA BASE; ELECTROENCEPHALOGRAPHY; GEOMETRY; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MENTAL TASK; NOISE REDUCTION; PRIORITY JOURNAL; SPATIAL WEIGHTING SCHEME; STATISTICAL CONCEPTS; BRAIN; HUMAN; PHYSIOLOGY; PROCEDURES;

ALGORITHMS; BRAIN; BRAIN-COMPUTER INTERFACES; CUES; ELECTROENCEPHALOGRAPHY; HUMANS;

EID: 85016571768     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2017.02.014     Document Type: Article

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