Research of P300 Feature Extraction Algorithm Based on Wavelet Transform and Fisher Distance
Автор: WANG Pan, SHEN Ji-Zhong, SHEN Jin-He
Журнал: International Journal of Education and Management Engineering(IJEME) @ijeme
Статья в выпуске: 6 vol.1, 2011 года.
Бесплатный доступ
With the aim to improve the divisibility of the features extracted by wavelet transform in P300 detection, we research the P300 frequency domain of event related potentials and the influence of mother wavelet selection towards the divisibility of extracted features, and then a new P300 feature extraction method based on wavelet transform and Fisher distance is proposed, which overcomes the drawbacks of no systematic feature selection method during traditional P300 feature extraction based on wavelet transform. In this paper, both the BCI Competition 2003 and the BCI Competition 2005 data sets of P300 were used for validation, the results showed that the proposed method can increase the divisibility by 121.8% of the features extracted by wavelet transform, and contribute to the followed classification.
BCI, Wavelet Transform, P300, Fisher Distance, Feature Extraction
Короткий адрес: https://sciup.org/15013632
IDR: 15013632
Список литературы Research of P300 Feature Extraction Algorithm Based on Wavelet Transform and Fisher Distance
- D.J. Krusienski, E.W. Sellers, T.M. Vaughan. Common Spatio-Temporal Patterns for the P300 Speller[A]. In: Proceedings of the 3rd international IEEE EMBS Conference on Neural Engineering[C]. Hawaii, USA. 2007. 421-424.
- Alexander Lenhardt, Matthias Kaper, Helge J. Ritter. An Adaptive P300-Based Online Brain–Computer Interface[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2008, 16(2): 121-130.
- Kana Omori, Tomonari Yamaguchi, Katsuhiro Inoue. Feature Extraction from EEG Signals in P300 Spelling System[A]. In: ICROS-SICE International Joint Conference 2009[C]. Fukuoka International Congress Center, Japan. 2009. 849-852.
- Mathew Salvaris, Francisco Sepulveda. Wavelet and Ensemble of FLDs for P300 Classification[A]. In: Proceedings of the 4rd international IEEE EMBS Conference on Neural Engineering[C]. Antalya, Turkay. 2009. 339-342.
- YANG Bang Hua, YAN Guo Zheng, YAN Bo. Extracting EEG Feature in Brain-computer Interface Based on Discrete Wavelet Transform [J]. Chinese Journal of Biomedical Engineering, 2006, 25(5): 518-522(in Chinese)
- WU Xiao Pei, YE Zhong Fu, GUO Xiao Jing, et al. Dynamic Independent Component Analysis and its Application to EEG of Motor Imagination[J]. Chinese Journal of Biomedical Engineering, 2007, 26(6): 818-824(in Chinese).
- Chan F, Lam F, POoh P, et al. Detection of brainstem auditory evoked potential by adaptive filtering[J]. Med Biol Eng Comput, 1995, 33(2): 69-75．
- Seyedehmina Ayoubian Markazi, Lampros.S.Stergioulas, Anusha Ramchurn, et al. Wavelet Filtering of the P300 Component in Event-Related Potentials[A]. In: Proceeding of the 28th IEEE EMBS Annual International Conference[C]. New York, USA. 2006. 1719-1722.
- YANG Li Cai, LI Jin Liang, YAO Yu Cui, et al. P300 Detection Algorithm Based on Wavelet Decomposition and Support Vector Machines[J]. Chinese Journal of Biomedical Engineering, 2007,26(6): 804-809(in Chinese).
- Hilit Serby, Elad Yom-Tov, Gideon F. Inbar. An Improved P300-Based Brain-Computer Interface[J]. IEEE Trans on Neural System and Rehabilitation Engineering, 2005,13(1): 89-98.
- WANG Da Kui, PENG Jin Ye. Wavelet Analysis and Application in Signal Processing [M]. Beijing: Publishing House of Electronics Industry, 2006.1(in Chinese).
- D. Huang, C. Xiang, S.S. Ge. Recursive Fisher Linear Discriminant for BCI Applications [A]. In: ISSNIP 2007 3rd International Conference [C]. Melbourne, Australia: 2007. 383-388.
- Ozair Idris Khan, Sang-Hyuk Kim, Adil Khan, et al. Extraction of P300 Using Constrained Independent Component Analysis[A]. In: 31st Annual International Conference of the IEEE EMBS[C]. Minnesota, USA. 2009. 4031-4034.
- Abeer E. Selim, Manal Abdel Wahed, Yasser M. Kadah. Machine Learning Methodologies in P300 Speller Brain-Computer Interface Systems[A]. In: 26rd National Radio Science Conference[C]. Future Univ, Egypt. 2009. 1-8.
