Electroencephalogram classification methods

• Autorzy: Prilepok M. , Jahan S. , Snasel V.

Warianty tytułu

PL

Metody klasyfikacji elektroencefalogramu

• Języki publikacji: EN

Abstrakty

EN

Today still big challenge in world to find efficient technique for perform recognition on mental tasks, and distinguish between them. This allow us to use Brain Computer Interface applications to helps disabled people to interaction with environment and control on external devices.

PL

Obecnie duze znacznie ma rozpoznawanie aktywności umysłowej dzięki analizie aktywności mózgu. W artykule omówiono interfejs komputer-mózg.

Słowa kluczowe

EN

EEG; Lempel-Ziv Complexity; EEG data; electroencefalograph

PL

elektroencefalograf; analiza danych; EEG

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2013
• Tom: R. 89, nr 11
• Strony: 51--54
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr.

Twórcy

autor

Prilepok M.

• VSB – Technical University of Ostrava

autor

Jahan S.

• VSB – Technical University of Ostrava

autor

Snasel V.

• VSB – Technical University of Ostrava

Bibliografia

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• [2] Ochoa J. B., Molina G. G., Ebrahimi T., EEG Signal Classification for Brain Computer Interface Applications, Ecole Polytechnique Federale De Lausanne, 2002
• [3] Sanei S., Chambers J. A., EEG Signal Processing, 2007, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England
• [4] Rutkowski T. M., Zdunek R., Cichocki A., Multichannel EEG brain activity pattern analysis in time-frequency domain with nonnegative matrix factorization support, International Congress Series, 2007, No. 1301, 266-269
• [5] David Skillicorn., Understanding Complex Datasets. 2007 by Taylor and Francis Group, LLC 54 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 89 NR 11/2013
• [6] Weixiang L., Nanning Z., and Xi L., Nonnegative Matrix Factorization for EEG Signal Classification, Advances in Neural Networks - ISNN 2004, International Symposium on Neural Networks, Dalian, China, 2004, 470 – 475
• [7] Lee H., Cichocki A., Choi S., Nonnegative Matrix Factorization for Motor Imagery EEG Classification, Artificial Neural Networks - ICANN 2006 16th International Conference, Athens, Greece, September 10-14, 2006, 250-259
• [8] Lee H., Kim Y., Cichocki A., Choi 6S., Nonnegative Tensor Factorization for Continuous EEG Classification, International Journal of Neural Systems, Vol. 17, No. 4 (2007), 305-317
• [9] Mingyu L., Hongbing J., Chunhong Z., Non negative Matrix Factorization and Its Application in EEG Signal Processing, Bioinformatics and Biomedical Engineering The 2nd International Conference, Xian, 2008, 2146-2148
• [10] Lee H., Choi S., CUR+NMF for Learning Spectral Features from Large Data Matrix, Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference, Pohang, 1592-1597
• [11] Lee H., Cichocki A., Choi S., Kernel nonnegative matrix factorization for spectral EEG feature extraction, 2009, 3182-3190
• [12] Lee H., Choi S., Group Nonnegative Matrix Factorization for EEG Classification,12th International conference on Artificial and Statistics (AISTATS), Florida, 2009, 320-327
• [13] Phan A. H., Cichocki A., Fast Nonnegative Tensor Factorization for Very Large-Scale Problems Using Two-Stage Procedure, Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 3rd IEEE International Workshop, 297-300
• [14] Lee H., Yoo J., Choi S., Semi-Supervised Nonnegative Matrix Factorization, Signal Processing Letters, IEEE, 2010, 4-7
• [15] Shin B., Oh A., Bayesian Group Nonnegative Matrix Factorization for EEG Analysis, CoRR dec 2012
• [16] Dohnalek p., Gajdos p., Peterek t., Penhaker M., Pattern Recognition in EEG Cognitive Signals Accelerated by GPU, International Joint Conference CISIS'12-ICEUTE'12-SOCO'12 Special Sessions Advances in Intelligent Systems and Computing Volume 189, 2013, 477–485
• [17] Abásolo D., Hornero, R., Gómez, C., García, M., López, M., Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure, Medical Engineering and Physics 28 (4) , 2006, 315-322
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• [28] Jahan I. S., Prilepok M., Snasel V., EEG Data Similarity Using Lempel–Ziv Complexity, unpublished