An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain-computer interface

Journal of Neural Engineering

Volumn 1, Issue 1, 2004, Pages 1-7

  Wang, Tao ^a   He, Bin ^a,b  

^a University of Illinois at Chicago   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BRAIN; ELECTROENCEPHALOGRAPHY; IMAGE SENSORS; INTERFACES (COMPUTER); MEDICAL PROBLEMS; SIGNAL PROCESSING;

BRAIN COMPUTER INTERFACE (BCI); FREQUENCY DECOMPOSITION; IMAGERY;

BIOSYNTHESIS;

ACCURACY; ALGORITHM; ARTICLE; BRAIN FUNCTION; CLASSIFICATION; COMPUTER INTERFACE; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAM; HAND MOVEMENT; HUMAN; IMAGERY; MENTAL FUNCTION; MOTOR PERFORMANCE; PRIORITY JOURNAL; RECOGNITION; RHYTHM; TRAINING; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL RHYTHM; BRAIN; CLINICAL TRIAL; CLUSTER ANALYSIS; COMMUNICATION AID; ELECTROENCEPHALOGRAPHY; EVOKED MUSCLE RESPONSE; IMAGINATION; INFORMATION RETRIEVAL; METHODOLOGY; PERIODICITY; PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOLOGICAL CLOCKS; BRAIN; CLUSTER ANALYSIS; COMMUNICATION AIDS FOR DISABLED; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, MOTOR; HUMANS; IMAGINATION; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; PERIODICITY; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; USER-COMPUTER INTERFACE;

EID: 8844283724     PISSN: 17412560     EISSN: None     Source Type: Journal    
DOI: 10.1088/1741-2560/1/1/001     Document Type: Article

References (27)

1. Anderson C W, Stolz E A and Shamsunder S 1998 Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks IEEE Trans. Biomed. Eng. 45 277-86
2. Babiloni F, Babiloni C, Carducci F, Fattorini L, Onorati P and Urbano A 1996 Spline Laplacian estimate of EEG potentials over a realistic magnetic resonance-constructed scalp surface model Electroenceph. Clin. Neurophysiol. 98 363-73
3. Babiloni F, Cincotti F, Bianchi L, Pirri G, Millán J d R, Mouriño J, Salinari S and Marciani M G 2001 Recognition of imagined hand movements with low resolution surface Laplacian and linear classifiers Med. Eng. Phys. 23 323-8
4. He B 1999 Brain electric source imaging: scalp Laplacian mapping and cortical imaging Crit. Rev. Biomed. Eng. 27 149-88
5. He B, Lian J and Li G 2001 High-resolution EEG: a new realistic geometry spline Laplacian estimation technique Clin. Neurophysiol. 112 845-52
6. Hjorth B 1975 An on-line transformation of EEG scalp potentials into orthogonal source derivations Electroenceph. Clin. Neurophysiol. 9 526-30
7. Jung T P, Makeig S, Humphries C, Lee T W, McKeown M J, Iragui V and Sejnowski T J 2000 Removing electroencephalographic artifacts by blind source separation Psychophysiology 37 163-78
8. Lagerlund T D, Sharbrough F W and Busacker N E 1997 Spatial filtering of multichannel electroencephalographic recordings through principal component analysis by singular value decomposition J. Clin. Neurophysiol. 14 73-82
9. Lugger K, Flotzinger D, Schlögl A, Pregenzer M and Pfurtscheller G 1990 Feature extraction for on-line EEG classification using principal components and linear discriminants Med. Biol. Eng. Comput. 36 309-14
10. McFarland D J, McCane L M, David S V and Wolpaw J R 1997 Spatial filter selection for EEG-based communication Electroenceph. Clin. Neurophysiol. 103 386-94
11. Millán J R, Mourino J, Franzé M, Cincotti F, Varsta M, Heikkonen J and Babiloni F 2002 A local neural classifier for the recognition of EEG patterns associated to mental tasks IEEE Trans. Neural Networks 13 678-86
12. Nunez P, Silibertein R B, Cdush P J, Wijesinghe R S, Westdrop A F and Srinivasan R 1994 A theoretical and experimental study of high resolution EEG based on surface Laplacian and cortical imaging Electroenceph. Clin. Neurophysiol. 90 40-57
13. Obermaier B, Guger C, Neuper C and Pfurtscheller G 2001 Hidden Markov models for online classification of single trial EEG data Pattern Recognit. Lett. 22 1299-309
14. Osman A and Robert A 2001 Time-course of cortical activation during overt and imagined movements Cognitive Neuroscience Annual Meeting (New York, 2001 March)
15. Papoulis A 1977 Signal Analysis (New York: McGraw-Hill)
16. Penny W D, Roberts S J, Curran E A and Stokes M J 2000 EEG-based communication: a pattern recognition approach IEEE Trans. Rehabil. Eng. 8 214-5
17. Perrin F, Bertrand O and Pernier J 1987 Scalp current density mapping: value and estimation from potential data IEEE Trans. Biomed. Eng. 34 283-8
18. Pfurtscheller G and Neuper C 2001 Motor imagery and direct brain-computer communication Proc. IEEE 89 1123-34
19. Pfurtscheller G, Neuper C, Flotzinger D and Pregenzer M 1997 EEG-based discrimination between imagination of right and left hand movement Electroenceph. Clin. Neurophysiol. 103 642-51
20. Pfurtscheller G, Neuper C, Schlögl A and Lugger K 1998 Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters IEEE Trans. Rehabil. Eng. 6 316-25
21. Pregenzer M, Pfurtscheller G and Flotzinger D 1996 Automated feature selection with a distinction sensitive learning vector quantizer Neurocomputing 11 19-29
22. Ramoser H, Müller-Gerking J and Pfurtscheller G 2000 Optimal spatial filtering of single trial EEG during imagined hand movement IEEE Trans. Rehabil. Eng. 8 441-6
23. Sajda P, Gerson A, Müller K R, Blankertz B and Parra L 2003 A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces IEEE Trans. Neural Systems Rehabil. Eng. 11 184-5
24. Wickelgren I 2003 Tapping the mind Science 299 496-9
25. Wolpaw J R and McFarland D J 1994 Multichannel EEG-based brain-computer communication Electroencephalogr. Clin. Neurophysiol. 90 444-9
26. Wolpaw J R, Birbaumer N, Heetderks W J, McFarland D J, Peckham P H, Schalk G, Donchin E, Quatrano L A, Robinson C J and Vaughan T M 2000 Brain-computer interface technology: a review of the first international meeting IEEE Trans. Rehabil. Eng. 8 164-73
27. Wolpaw J R, Birbaumer N, McFarland D J, Pfurtscheller G and Vaughan T M 2002 Brain-computer interfaces for communication and control Clin. Neurophysiol. 113 767-91