本論文提出一個有效的方法，對受測者在意圖抬起左手小指頭與意圖吐舌頭時的腦電波做辨識。腦電波辨識是否成功的關鍵，在於特徵擷取與分類兩個議題。過去文獻將重點放在分類演算法的改良上，然而找出更簡單而重要的特徵，也可以獲得高辨識率。對角化主要成份分析法(DiaPCA)可以從腦電波高維度的時-頻-空域資料矩陣中找出主要的成份。被挑選出來的主要成份可構成一個較低維度的特徵矩陣，但仍保有兩種想像動作的腦電波之間主要的特徵差異。因此，藉由計算特徵矩陣間的歐氏距離就可分類腦電波。這個方法比起其他分類演算法，如支持向量機(SVM)，不但較為簡單，而且不會降低辨識率。本論文提出利用「改良式對角化主成份分析法」對腦電波擷取特徵並辨識，結果顯示，腦電波辨識的準確率大幅提升了10.07%。

參考文獻
[1] Guest Editors, “Guest Editorial the Third International Meeting on Brain-Computer Interface Technology: Making a Difference,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 126-127, June, 2006.
[2] F. Cincotti, L. Bianchi, G. Birch, C. Guger, J. Mellinger, R. Scherer, R. N. Schmidt, O. Y. Suárez, and G. Schalk, “BCI Meeting 2005—Workshop on Technology: Hardware and Software,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 128-131, June, 2006.
[3] A. Kübler, V. K. Mushahwar, L. R. Hochberg, and J. P. Donoghue “BCI Meeting 2005—Workshop on Clinical Issues and Applications,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 131-134, June, 2006.
[4] R. Caton, “The electric currents of the brain,” British Medical Journal, Vol. 2, pp 278, 1875.
[5] H. Berger, “Über das Elektrenkephalogramm des Menschen,” European Archives of Psychiatry and Clinical Neuroscience, Vol. 87, pp 527-570, December, 1929.
[6] http://www.dls.ym.edu.tw/neuroscience/functional_c.htm
[7] H. Jasper, “Report of committee on methods of clinical exam in EEG,” Electroencephalogr. Clin. Neurophysiol., 10: 370-375, 1958.
[8] http://faculty.washington.edu/chudler/1020.html
[9] L. Hu, B. H. Jansen, and N. N. Boutros, “Is P50 an epiphenomenon?” Proc. of 27st Annual International Conference of the IEEE EMBS, Shanghai, China, pp 1166-1169, September, 2005.
[10] 曾坤章，“你開悟了嗎?遠離豬頭擁抱佛陀，”小海豚意識科技，2006。
[11] J. Bhattacharya and H. Petsche, “Phase Synchrony analysis of EEG during music perception reveals changes in functional connectivity due to musical expertise,” Signal Processing, Vol. 85, pp 2161-2177, July, 2005.
[12] J. W. Kozelka and T. A. Pedley, “Beta and mu rhythms,” J. Clin. Neurophysiol., Vol. 7(2), pp 191-207, 1990.
[13] S. Sutton, M. Braren, J. Zubin, and E. R. John, ” Evoked-potential correlates of stimulus uncertainty,” Science, Vol. 150, pp 1187–1188, 1965.
[14] T. M. Vaughan, D. J. McFarland, G. Schalk, W. A. Krusienski, D. J., E.W. Sellers, J. R. Wolpaw, “The wadsworth BCI research and development program: at home with BCI,” IEEE Trans. Neural Syst. Rehabil. Eng., Vol. 14, no. 2, pp 229-233, June, 2006.
[15] L. J. Trejo, R. Rosipal ,and B. Matthews, “Brain-computer interfaces for 1-D and 2-D cursor control: Designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 14, no. 2, pp 225-229, June, 2006.
[16] D. Zhang, Z. H. Zhou, and S. Chen “Diagonal principal component analysis for face recognition,” Pattern Recognition, Vol. 39, pp 140-142, January, 2006.
[17] J. R. Wolpaw and D. J. McFarland, “Control of a two-dimensional movement signal by a non-invasive brain-computer interface in humans,” Proc. Natl. Acad. Sci. USA, Vol. 101, pp 17849-17854, 2004.
[18] R. Leeb and G. Pfurtscheller, “Walking through a Virtual City by Thought,” Proc. of 26st Annual International Conference of the IEEE EMBS, San Francisco, CA, USA, pp 4503-4506, September, 2004.
[19] D. J. McFarland, C. W. Anderson, K. R. Müller, A. Schlögl, and D. J. Krusienski, “BCI Meeting 2005—Workshop on BCI Signal Processing: Feature Extraction and Translation,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 135-138, June, 2006.
[20] D. Hao, H. Zhang, and N. Yu, ”High Resolution Time-Frequency Analysis for Event-Related Electroencephalogram,” Proc. of 6st World Congress on Intelligent Control and Automation Conference of the IEEE EMBS, Dalian, China, pp 9473-9476, June, 2006.
[21] N. Yamawaki, C. Wilke, Z. Liu, and B. He, “An enhanced time-frequency-spatial approach for motor imagery classification,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 250-254, June, 2006.
[22] Y. Li, A. Cichocki, C. Guan and J. Qin, “Sparse Factorization Preprocessing-Based Offline Analysis for a Cursor Control Experiment,” IEEE International Workshop on Biomedical Circuits & Systems, Singapore, pp S3/5/INV5-8, December, 2004.
[23] H. Zhang, C. Guan, and Y. Li, “Signal processing for brain-computer interface: enhance feature extraction and classification,” Proc. ISCAS, pp 1615-1618, May, 2006.
[24] N. J. Hill, T. N. Lal, M. Schröder, T. Hinterberger, B. Wilhelm, F. Nijboer, U. Mochty, G. Widman, C. Elger, B. Schökopf, A. Kübler ,and N. Birbaumer, “Classifying EEG and ECoG Signals without Subject Training for Fast BCI Implementation: Comparison of Non-Paralysed and Completely Paralysed Subjects,” IEEE Trans. Rehabil. Eng., Vol. 14, no. 2, pp 183-186, June, 2006.
[25] R. Palaniappan, R. Paramesran, S. Nishida, and N. Saiwaki, “A New Brain–Computer Interface Design Using Fuzzy ARTMAP,” IEEE Transactions on Neural Systems And Rehabilitation Engineering, Vol. 10, no. 3, pp 140-148, Sep. 2002.
[26] A. M. Walker, “Some consequences of superimposed error in time series analysis,’ Biomerrica, Vol. 47, pp 33-43, 1966.
[27] 劉勇均，“應用於指動偵測之腦波訊號分析系統，”國立成功大學資訊工程所碩士論文，2004。
[28] S. Theodoridis and K. Koutroumbas,“Pattern Recognition,”ACADEMIC PRESS, second edition, 2003.
[29] K. Yang and C. Shahabi, “On the stationarity of multivariate time series for correlation-based data analysis,” Proc. of 5fth IEEE International Conference on Data Mining, Houston, Texas, November, 2005.
[30] J. W. Cooley and J. W. Tukey, “An algorithm for the machine calculation of complex Fourier series,” Math. Comput., Vol. 19, pp 297-301, April, 1965.
[31] 李天龍，“以FFT為架構建立之諧波參數建立方法，”中山大學電機工程學系研究所碩士論文，1999。
[32] 洪至懿，“特徵擷取與分類應用與想像左右手手指運動之腦波辨識，”陽明大學放射醫學科學研究所碩士論文，2003。
[33] T. N. Lal, T. Hinterberger, G. Widman, M. Schröder, J. Hill, W. Rosenstiel, C. E. Elger, B. Schölkopf, N. Cirbaumer, L. K. Saul, Y. Weiss, and L. Bottou, “Methods towards invasive human brain computer interfaces,” Advances in Neural Information Processing Systems (NIPS) 17, Cambridge, MA: MIT Press, pp 737–744, 2005.
[34] K. Fukunaga ,and D. M. Hummels, “Leave-One-Out Procedures for Nonparametric Error Estimates,” IEEE Trans. Parrern Anal. Machine Intell., Vol. 11, no. 4, pp 421-423, April, 1989.