ICA-SVM combination algorithm for identification of motor imagery potentials

CIMSA 2010 - IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, Proceedings

Volumn , Issue , 2010, Pages 92-96

  Ming, Dong ^a   Sun, Changcheng ^a   Cheng, Longlong ^a   Bai, Yanru ^a   Liu, Xiuyun ^a   An, Xingwei ^a   Qi, Hongzhi ^a   Wan, Baikun ^a   Hu, Yong ^b   Luk, Kdk ^b  

^a TIANJIN UNIVERSITY   (China)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Brain computer interface (BCI); ERD ERS coefficient; Event related desynchronization synchronous (ERD ERS); Independent component analysis (ICA); Power spectral density (PSD); Support vector machine (SVM)

Indexed keywords

ACCURACY RATE; CLASSIFICATION METHODS; EFFECTIVE TOOL; ERD/ERS; EVENT RELATED DESYNCHRONIZATION; EVENT-RELATED SYNCHRONIZATIONS; INDEPENDENT COMPONENTS; MENTAL TASKS; MOTOR IMAGERY; POWER SPECTRAL DENSITY (PSD); SIGNAL EXTRACTION; SUPPORT VECTOR MACHINE (SVM);

ARTIFICIAL INTELLIGENCE; INDEPENDENT COMPONENT ANALYSIS; INTERFACES (COMPUTER); MEASUREMENTS; POWER SPECTRAL DENSITY; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES;

BRAIN COMPUTER INTERFACE;

EID: 78649543244     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIMSA.2010.5611755     Document Type: Conference Paper

References (14)

1. Wolpaw JR, Birbaumer N, McFarland D.J., Pfurtscheller G., and Vaughan T M. "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, pp. 767-791, 2002.
2. Leeb R, Lee F, Keinrath C., Scherer R, Bischof H, Pfurtscheller G., "Brain-computer communication: motivation, aim, and impact of exploring a virtual apartment," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 15, no. 4, pp. 473-482, December 2007.
3. Nijboer F, Furdea A, Gunst I., Mellinger J, McFarland DJ, Birbaumer N, et al, "An auditory brain-computer interface (BCI)," J. Neurosci. Methods, vol. 167, no. 1, pp. 43-45, January 2008.
4. Schalk G, Brunner P, Gerhardt L.A., Bischof H., Wolpaw JR, "Brain-computer interfaces (BCIs): detection instead of classification" J. Neurosci. Methods, vol. 167, no. 1, pp. 51-62, January 2008.
5. Hsu WY, "EEG-based motor imagery classification using neuro-fuzzy prediction and wavelet fractal features," J. Neurosci. Methods, April 2010.
6. Pei XM, Zheng CX, Xu J, Bin G.Y., Wang HW, "Multi-channel linear descriptors for event-related EEG collected in brain computer interface," J. Neural Eng., vol. 3, no. 1, pp. 52-58, February 2006.
7. Neuper C, Scherer R, Wriessnegger S., Pfurtscheller G, "Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface," Clin. Neurophysiol., vol. 120, no. 2, pp. 239-247, February 2009.
8. Pfurtscheller G, Neuper C, Flotzinger D., Pregenzer M, "EEG-based discrimination between imagination of right and left hand movement," Electroencephalogr. Clin. Neurophysiol., vol. 103, no. 6, pp. 642-651, December 1997.
9. Lemm S, Schäfer C, Curio G., "BCI Competition 2003 - Data set III: probabilistic modeling of sensorimotor mu rhythms for classification of imaginary hand movements," IEEE Trans. Biomed Eng., vol. 51, no. 6, pp. 1077-1080, June 2004.
10. Li K, Sankar R, Arbel Y., Donchin E, "Single trial independent component analysis for P300 BCI system," Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 4035-4038, 2009.
11. Patel A, Alotaibi F, Blume W.T., Mirsattari SM, "Independent component analysis of subdurally recorded occipital seizures," Clin. Neurophysiol., vol. 119, no. 11, pp. 2437-2446, November 2008.
12. Wan BK, Zhou ZX, Ming D, Qi H.Z., "Detection of ERD/ERS Signals Based on ICA and PSD," J. Tianjin Univ, vol. 41, no. 11, pp. 1383-1390, November 2008.
13. Demirer RM, Ozerdem MS, Bayrak C, "Classification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution," J. Neurosci. Methods, vol. 178, no. 1, pp. 214-218, March 2009.
14. Xu Q, Zhou H, Wang Y., Huang J, "Fuzzy support vector machine for classification of EEG signals using wavelet-based features," Med. Eng. Phys., vol. 31, no. 7, pp. 858-865, May 2009.