穩態視覺誘發電位於大腦人機介面之刺激頻率及責任週期設計

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姓名

梁家銘(Jia-Ming Liang) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

穩態視覺誘發電位於大腦人機介面之刺激頻率及責任週期設計
(Stimulation Frequency and Duty Ratio Design in SSVEP-Based BCI System)

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摘要(中)

本篇論文針對穩態視覺(Steady-State Visual Evoked Potentials, SSVEP)誘發電位之腦電訊號處理，設計一數位訊號處理硬體電路，實現具即時性的大腦人機介面系統(Brain Computer Interface, BCI)。可以有效改善目前相關研究必須建構於使用個人電腦搭配線上訊號處理軟體，以及資料擷取卡等的高成本實現方式。本研究以場可程式邏輯閘陣列(Field Programmable Gate Array, FPGA)為基礎來設計相關電路並實現穩態視覺誘發電位之硬體即時訊號處理，用以建立低成本與方便使用之BCI系統。另外，為了有效誘發SSVEP之腦電訊號，本篇論文設計發光二極體(Light-emitting diode, LED)閃爍燈號可依不同使用者之腦波反應特性，自我制定閃爍頻率以及燈號觸發責任週期，來有效誘發使用者的SSVEP，以增強訊號之訊雜比，而提高系統判斷率。最後經由實驗結果證明本系統能有效誘發出使用者之 SSVEP，達到即時SSVEP訊號辨識處理，並且能有高準確辨識率。

摘要(英)

This thesis proposes a low-cost field-programmable gate-array (FPGA) based steady state visual evoked potential (SSVEP) brain-computer interface (BCI) system. Most existing BCI systems use bulky and expensive electroencephalography (EEG) measurement equipment, personal computer, and commercial real-time signal-processing software. Therefore, the objective of this thesis is to establish a low cost FPGA-based BCI system with real-time SSVEP signal processing circuit. Moreover, the flashing duty and frequency of LED flicker are choose by an automatically searching procedure for each user in order to evoke SSVEP signal effectively and improves the information transfer rate (ITR). Finally, experimented results show that the SSVEP can be evoked effectively and high identification accuracy is obtained.

關鍵字(中)

★ 穩態視覺誘發電位
★ 大腦人機介面
★ 閃光頻率
★ 責任週期

關鍵字(英)

★ EEG
★ flicker frequency
★ duty ratio
★ phase encoding
★ BCI
★ SSVEP

論文目次

摘要................................................I
Abstract............................................II
誌謝................................................III
目錄................................................IV
圖目錄..............................................VIII
表目錄..............................................XI
第一章　緒論........................................1
1.1 研究動機........................................1
1.2 研究目的與方法..................................2
1.3 論文大綱........................................3
第二章以穩態視覺誘發電位為基礎之大腦人機介面.......4
2.1 大腦人機介面系統................................4
2.2 視覺誘發電位....................................5
2.3 SSVEP-Based BCI系統.............................7
2.4 兩頻四相位編碼技術..............................9
第三章　閃光刺激頻率及責任週期決策..................12
3.1 SSVEP能量之變化因素.............................12
3.2 閃光刺激頻率決策................................13
3.3 閃光責任週期決策................................18
3.4 使用者刺激閃光設計..............................22
第四章　量測系統電路設計............................29
4.1量測系統電路架構.................................29
4.2 訊號處理系統架構................................30
4.2.1 交流耦合網路..................................30
4.2.2 前級差動放大器................................34
4.2.3 電感電容式陷波濾波器..........................37
4.2.4 四階帶通濾波器................................40
4.2.5 陷波濾波器....................................44
4.2.6 自動倍率調整與箝位電路........................46
4.3 數位訊號處理系統之硬體實現......................50
4.3.1 數位濾波器....................................51
4.3.2 平均技術......................................52
4.3.3 相位角、振幅能量運算..........................53
4.3.4 使用者閃光決策模式、最佳化模式以及應用模式....54
4.3.5 生理回饋系統..................................57
第五章　系統硬體模擬與實驗結果......................58
5.1 系統規格與時間分析..............................58
5.2 數位硬體驗證....................................62
5.2.1 數位濾波器與平均技術之硬體驗證................63
5.2.2 系統硬體邏輯單元之消耗程度....................68
5.2.3 相位辨識......................................69
5.3 大腦人機介面系統實驗與分析......................73
5.4 實驗結果討論....................................78
第六章　結論與未來展望..............................80
參考文獻............................................81

參考文獻

[1] M. Cheng, X. Gao, S. Gao, and D. Xu, “Design and Implementation of a Brain-Computer Interface With High Transfer Rates,” IEEE Trans. Biomed. Eng., Vol. 49, No. 10, Oct., 2002.
[2] G. Schalk, D. J. McFarland, T. Hinterberger, N. Birbaumer, and J. R. Wolpaw, “BCI2000: A General-Purpose Brain-Computer Interface (BCI) System,” IEEE Trans. Biomed. Eng., Vol. 51, No. 6, Jun., 2004.
[3] 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 Trans. Neural Syst. Rehab. Eng., Vol. 14, No. 2, Jun., 2006.
[4] Y. Wang, R. Wang, X. Gao, B. Hong, and S. Gao, “A Practical VEP-Based Brain-Computer Interface,” IEEE Trans. Neural Syst. Rehab. Eng., Vol. 14, No. 2, Jun., 2006.
[5] X. Gao, D. Xu, M. Cheng, and S. Gao, “A BCI-based environmental controller for the motion-disabled,” IEEE Trans. Rehab. Eng., vol. 11, no. 2, pp. 137–140, Jun. 2003.
[6] C. S. Herrmann, “Human EEG responses to 1–100 Hz flicker: Resonance phenomena in visual cortex and their potential correlation to cognitive phenomena,” Exp. Brain Res., Vol. 137, pp. 346–353, 2001.
[7] S. Kalitzin, J. Parra, D. N. Velis, and F. H. Lopes da Silva, “Enhancement of Phase Clustering in the EEG/MEG Gamma Frequency Band Anticipates Transitions to Paroxysmal Epileptiform Activity in Epileptic Patients With Known Visual Sensitivity,”IEEE Trans. Biomed. Eng., Vol. 49, no. 11, Nov. 2002.
[8] Z. H. Wu, “The Difference of SSVEP Resulted by Different Pulse Duty-cycle,” IEEE Conf., 2009.
[9] 賴仁傑， “具增益自動調整之穩態視覺誘發電位量測電路研製” ，國立中央大學電機工程學系，碩士論文，民國九十八年六月。
[10] 松井邦彥， “OP放大器應用技巧100例” ，科學出版社，12頁，西元2005年。
[11] J. C. Huhta and J. G. Webster, “60-Hz Interference in Electro-Cardiography”, IEEE Trans. Biomed. Eng., Vol. BME-20, pp. 91–101, Mar. 1973.
[12] 黃進強， “交流耦合平衡增益之腦波量測系統” ，國立中央大學電機工程學系，碩士論文，民國九十六年七月。
[13] E. M. Spinelli, P. Areny, and M. A. Mayosky, “AC-Coupled Front-End for Biopotential Measurements,” IEEE Trans. Biomed. Eng., Vol. 50, No.3, pp.391-395, Mar., 2003.
[14] Burr-Brown Corporation, INA128 Datasheet, Oct. 1996.
[15] 盧明智，黃敏祥， “OP Amp 應用+實驗模擬” ，全華科技圖書股份有限公司，243-279、451-544頁，民國八十四年十二月。
[16] P.L. Lee, C.H. Wu, J.C. Hsieh, and Y.T. Wu, “visual evoked potemtial actuated brain computer interface: a brain-actuated cursor system”, Electronics Letters, vol. 41, No. 15, July, 2005.
[17] 謝竣傑，“多頻相位編碼之閃光視覺誘發電位驅動大腦人機介面”，國立中央大學電機工程學系，碩士論文，民國九十六年七月。
[18] 程湘君，「信號與系統」，儒林圖書有限公司，民國八十五年五月。
[19] Bhaskar D. Rao, “Floating Point Arithmetic and Digital Filters,” IEEE Trans. Signal Proc., Vol. 40, No. 1, Jun., 1992.
[20] A. Golmohammadi, M.T. Manzuri and S. Ayat, “A new pipeline implementation of an adaptive IIR filter for noise reduction application,” in Proc. IEEE Conf. ISCIT., Vol. 1, Oct., 2004.
[21] R.Jr Landry, V. Calmettes and E. Robin, “High speed IIR filter for XILINX FPGA,” in Proc. IEEE Conf. MWSCAS., Aug., 1998.
[22] Microchip Technology Inc., MCP3201 Datasheet, Jan. 2008.
[23] E. C. Lalor, S. P. Kelly, C. Finucane, R. Burke, R. Smith, R. B. Reilly, and G. McDarby, “Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment,” EURASIP J. Appl. Signal Process., 19, pp. 3156-3164, 2005.
[24] O. Friman, I. Volosyak, and A. Gräser, “Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces,” IEEE Trans. Biomed. Eng., Vol. 54, No. 4, Apr., 2007.
[25] J. V. Odom, M. Bach, C. Barber, M. Brigell, M. F. Marmor, A. P. Tormene, G. E. Hoder, and Vaegan, “Visual Evoked Potentials Standard,” Doc. Ophthalmol., 108, pp. 115-123, 2004.
[26] E. E. Sutter, “The Brain Response Interface: Communication through Visually-Induced Electrical Brain Response,” J. Microcomput. Appl., Vol. 15, pp. 31-45, 1992.
[27] Cyclone II Device Handbook, Altera, Inc., San Jose, CA, 2007.
[28] L.A. Farwell, E. Donchin,“Talking off the top of your head:A mental prosthesis utilizing event-related brain potentials,” Electroenceph Clin. Neurophysiol., Vol. 70, Dec., 1988.
[29] A. Luo, T. J. Sullivan,“A user-friendly SSVEP-based brain-computer interface using a one-channel dry-electrode EEG device,” Neural Engineering., Vol.7, 2010.
[30] J. Pan, X. Gao, F. Duan, Z. Yan, and S. Gao,“Enhancing the classification accuracy of steady-state visual evoked potential-based brain–computer interfaces using phase constrained canonical correlation analysis,” Neural Engineering., Vol.8, No.3, May, 2011.

指導教授

徐國鎧(Kuo-kai Shyu)

審核日期

2011-8-1

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