A STATISTICAL FEATURE EXTRACTION IN WAVELET DOMAIN FOR MOVEMENT CLASSIFICATION: A CASE STUDY FOR EYES OPEN, EYES CLOSED, AND OPEN/CLOSED FIST TASKS

Yıl 2018, Cilt: 8 Sayı: 2, 158 - 162, 30.11.2018

Şükriye Kara Semih Ergin

Öz

Analysis of brain signals constitute an importance,
especially for paralyzed people or people suffer from motor disabilities. For
this aim, some studies have been evaluated to measure signals from the scalp to
provide non-muscle control arguments. Brain-Computer Interface Systems turns
these signals into device signals that are controllable at the level of
thought. In this paper, we classify diverse tasks according to EEG
(electroencephalogram) signals. Then pre-processing, feature extraction and
classification steps are hold. For classification, we use FLDA, Linear SVM,
Quadratic SVM, PCA, and k-NN methods. The best result is obtained by using
k-NN.

Anahtar Kelimeler

EEG, electroencephalogram, wavelet transform, feature extraction, classification

Kaynakça

• [1] Farwell, L. A. and Donchin, E. (Dec. 1988). Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials. Electroen- ceph. Clin. Neurophysiol., vol. 70, no. 6, pp. 510–523, Dec. 1988. [2] Wolpaw, McFarland, D. J. , Neat, G. W. and, Forneris, C. A. (Mar. 1991). An EEG-based brain-computer interface for cursor control. Electroenceph. Clin. Neurophysiol., vol. 78, no. 3, pp. 252–259. [3] Sutter, E. E. (1992). The brain response interface: Communication through visually guided electrical brain responses. J. Microcomput. Applicat., vol. 15, pp. 31–45. [4] McFarland, D. J., Neat, G. W. and, Wolpaw, J. R. (1993). An EEG-based method for graded cursor control. Psychobiol., vol. 21, pp. 77–81. [5] Pfurtscheller, Flotzinger, D. and, Kalcher, J. (1993). Brain-computer inter- face—A new communication device for handicapped persons. J. Mi- crocomput. Applicat., vol. 16, pp. 293–299. [6] Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kubler, A., Perelmouter, J., Taub, E. and, Flor, H. (Mar. 1999). A spelling device for the paralyzed. Nature, vol. 398, no. 6725, pp. 297–298. [7] Kubler, A., Kotchoubey, B., Hinterberger, T., Ghanayim, N., Perel- mouter, J., Schauer, M., Fritsch, C., Taub, E. and, Birbaumer, N. (Jan. 1999) The thought translation device: A neurophysiological approach to communication in total motor paralysis. Exp. Brain Res., vol. 124, no. 2, pp. 223–232. [8] Kennedy, P. R., Bakay, R. A., Moore, M. M., and Goldwaithe, J. (June 2000). Direct control of a computer from the human central nervous system. IEEE Trans. Rehab. Eng., vol. 8, pp. 198–202. [9] Schalk, G., McFarland, D.J., Hinterberger, T., Birbaumer, N., Wolpaw, J.R., (2004). BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE Transactions on Biomedical Engineering 51(6): 1034-1043. [10] Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, PCh., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C-K, Stanley, H.E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation, 101(23): e215-e220 [Circulation Electronic Pages]. [11] Cengiz, Y., Doç, Y., Ariöz, U. (2016). Ayrik dalgacik dönüsümü kullanarak konusma sinyallerinin gürültüden arindirilmasi için uygulama: An application for speech denoising using discrete wavelet transform [pdf]. Retrieved from https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7849377 [12] Misiti, M., Misiti, Y., Oppenheim G. and, Poggi, J. (2007). Wavelets and their Applications. https://doi.org/10.1002/9780470612491 [13] Gupta, V., Mahle, R. and, Shriwas, R. S. (2013). Image denoising using wavelet transform method. Tenth International Conference on Wireless and Optical Communications Networks (WOCN), Bhopal, pp. 1-4, 2013. [14] Shannon, Claude E. (July-October 1948). A mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379-423. [15] Sen, B., Peker, M., Cavusoglu, A., Celebi, F.V. (2014). A Comparative Study on Classification of Sleep Stage Based on EEG Signals Using Feature Selection and Classification Algorithms. Journal of Medical Systems, 38(3)