變頻相位編碼於視覺誘發電位之大腦人機介面設計

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：50

、訪客IP：3.145.105.91

姓名

林冠宇(Kuan-yu Lin) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

變頻相位編碼於視覺誘發電位之大腦人機介面設計
(Visual Evoked Potential of BCI System based on Frequency-Modulated with Multi-Phase coding)

相關論文

★ 感光式觸控面板設計	★ 單級式直流無刷馬達系統之研製
★ 單級高功因LLC諧振電源轉換器之研製	★ 多頻相位編碼於穩態視覺誘發電位之大腦人機介面系統設計
★ 類神經網路於切換式磁阻馬達轉矩漣波控制之應用	★ 感應馬達無速度感測之直接轉矩向量控制
★ 具自我調適導通角度功能之切換式磁阻馬達驅動系統---DSP實現	★ 感應馬達之低轉速直接轉矩控制策略
★ 加強型數位濾波器設計於主動式噪音控制之應用	★ 非匹配不確定可變結構系統之分析與設計
★ 無刷直流馬達直接轉矩控制方法之轉矩漣波改善	★ 無轉軸偵測元件之無刷直流馬達驅動器研製
★ 無轉軸偵測元件之開關磁阻馬達驅動系統研製	★ 感應馬達之新型直接轉矩控制研究
★ 同步磁阻馬達之性能分析及運動控制研究	★ 改良比例積分與模糊控制器於線性壓電陶瓷馬達位置控制

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

有別於穩態視覺誘發電位以定頻弦波為大腦人機介面的誘發訊號，Chirp視覺誘發電位以chirp訊號作選項閃光依據，本論文利用chirp訊號的頻率會隨時間線性變化的特性以及各選項閃爍時間與休息時間的交錯，設計變頻相位編碼的大腦人機介面。
Chirp視覺誘發電位使用的分析方法為分數傅立葉轉換，為了讓轉換公式在實現上更加有效率，本論文使用快速傅立葉轉換來實現分數傅立葉轉換以簡化實現的複雜度。
為了使視覺誘發電位的數位濾波器不需因為chirp訊號的變頻特性而使用過寬的通帶，本論文提出一方法來實現可線性調變通帶的帶通濾波器，其核心是使用分數卷積，達成在不同時間有不同通帶的數位濾波器並且能與chirp訊號的瞬時頻率匹配，此方法能提高系統的訊號雜訊比，進而提高大腦人機介面的辨識正確率。

摘要(英)

This study implements a brain computer interface which is based on Chirp visual evoked potential. Because Chirp-VEP is not a sinusoid but a chirp signal, the phase-shift coding approach in this study would let each command has various instantaneous frequency at any time.
Fractional Fouier Transform can analyze the characteristic of linear frequency modulation, but its computation takes a lot of time. A mothed in this study implements FrFT via FFT so that the complexity can be reduced.
Unlike the unsuitable passband on a normal band-pass filter, the frequency-modulated passband can match the frequency of Chirp-VEP with time. It means that the filter completed by Fractional Convolution in this study has higher Signal-to-Noise Ratio than traditional filter. The experiment results demonstrate that the Chirp-VEP induced by the proposed method do have great accuracy and can be used in the BCI system.

關鍵字(中)

★ 大腦人機介面
★ 穩態視覺誘發電位
★ Chirp視覺誘發電位
★ 分數傅立葉轉換
★ 分數卷積

關鍵字(英)

★ Brain-Computer Interface(BCI)
★ Chirp Visual Evoked Potential (Chirp-VEP)
★ Fractional Fouier transform (FrFT)
★ Fractional Convolution

論文目次

摘要 i
Abstract ii
謝誌 iii
目錄 iv
圖目錄 vi
表目錄 x
第一章緒論 1
1-1 前言 1
1-2 研究目的與方法 1
1-3 論文架構 2
第二章變頻相位編碼之大腦人機介面 3
2-1 視覺誘發電位之大腦人機介面 3
2-2 暫態視覺誘發電位、穩態視覺誘發電位 5
2-3 Chirp視覺誘發電位 6
2-4 Chirp訊號數位化實現 9
2-5 Chirp訊號之相位調變 19
第三章分數傅立葉轉換 24
3-1 分數傅立葉轉換定義 24
3-2 Chirp訊號之分數傅立葉轉換 27
3-3 分數傅立葉轉換相關特性 28
3-4 分數傅立葉轉換與傅立葉轉換的關係 32
第四章分數卷積 36
4-1 分數卷積定義 36
4-2 分數卷積的分數傅立葉轉 38
4-3 分數卷積之無限脈衝響應濾波器 42
第五章實驗結果 49
5-1 刺激訊號數位化之分析 49
5-2 分數傅立葉轉換快速演算法之分析 53
5-3 Chirp視覺誘發電位非即時分析 55
5-4 Chirp視覺誘發電位即時之比較與分析 80
第六章結論與未來展望 83
參考文獻 85

參考文獻

[1] G. Schalk, D.J. McFarland, T. Hinterberger, N. Birbaumer, and J. R. Wolpaw, “BCI2000: A General-Purpose Brain-Computer Interface (BCI) System”, IEEE Transactions on Biomedical Engineering, Vol. 51,pp. 1034-1043, No. 6, June 2004.
[2] L. J. Trejo, R. Rosipal, and B. Matthews, “Brain–Computer Interfaces for 1-D and 2-D Cursor: Designs Using Volitional Control of the EEGSpectrum or Steady-State Visual Evoked Potentials”, IEEE Transactions on Neural System and Rehabilitation Engineering, Vol. 14, No. 2, pp. 225-229,June 2006.
[3] M. Cheng, X. R. Gao, S. K. Gao, and D. F. Xu,“Design and Implementation of a Brain-Computer Interface with High Transfer Rates”, IEEE Transactions on Biomedical Engineering, Vol. 49, No. 10, pp. 1181-1186, Oct. 2002.
[4] R. C. Panicker, S. Puthusserypady, and Y. Sun, “An Asynchronous P300 BCI with SSVEP-Based Control State Detection”, IEEE Transactions on Biomedical Engineering, Vol. 58, No. 6, pp. 1781-1788, June 2011.
[5] P. L. Lee, J. J. Sie, Y. J. Liu, C. H. Wu, M. H. Lee, C. H. Shu, P. H. Li, C. W. Sun, and K. K. Shyu, “An SSVEP-Actuated Brain Computer Interface Using Phase-Tagged Flickering Sequences: A Cursor System”, Annals of Biomedical Engineering, Vol. 38, No. 7, pp. 2383-2397, July 2010.
[6] H. Cecotti and A. Gräser, “Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 3, Mar. 2011.
[7] J. V. Odom, M. Bach, M. Brigell, G. E. Holder, D. L. McCulloch, A. P. Tormene, Vaegan, “ISCEV Standard for Clinical Visual Evoked Potentials(2009 update)”, Doc. Ophthalmol., 120, pp. 111-119, 2010.
[8] E. E. Sutter, “The Brain Response Interface: Communication through Visually-Induced Electrical Brain Response”, Journal of Microcomputer Application, Vol. 15, pp. 31-45, Jan. 1992.
[9] R.Sivakumar, “Analysis of Transient Visual Evoked Potential at Different Rate of Stimulation, ” 2009 Second Int. Conf. Comp. Elec. Eng.
[10] S. M. Lai, Z. Zhang, Y. S. Hung, Z. Niu, and C. Chang, “A Chromatic Transient Visual Evoked Potential Based Encoding / Decoding Approach for Brain–Computer Interface, ” IEEE J. Emerg. Select. Top. Circuits Syst., Vol. 1, No. 4, Dec. 2011.
[11] L. M. ai, Z. F. kun and Y. J. fu, “The Feature Extraction and Recognition of Transient Visual Evoked Potential Based on Wavelet Transform,” Biomed. Eng. Comp. Sci. (ICBECS), 2010 Int. Conf.
[12] 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.
[13] P. L. Lee, C. H. Wu, J. C. Hsieh, and Y. T. Wu,“Visual Evoked Potential Actuated Brain Computer Interface: A Brain-Actuated Cursor System”, Electronics Letters, Vol. 4, No. 15, July 2005.
[14] 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。
[15] 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 Journal on Applied Signal Processing, 19, pp. 3156-3164, 2005.
[16] Y. Wang, R. Wang, X. R. Gao, B. Hong and S. K. Gao, “A Practical VEP-Based Brain-Computer Interface”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 14, No. 2, pp. 234-239, June 2006.
[17] T. Tu, Y. Xin, X. Gao and S. Gao, “Chirp-modulated visual evoked potential as a generalization of steady state visual evoked potential,” IOP Publishing J. Neural Eng. 9 (2012) 016008 (11pp)
[18] 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.
[19] 彭韶驊，「Chirp視覺誘發電位為基礎之大腦人機介面-FPGA實現」，國立中央大學電機工程學系，碩士論文，民國一○二年六月。
[20] A. I. Zaye, “On the relationship Between the Fourier Transforms and Fractional Fourier Transforms,” IEEE Signal Processing Letter, Vol. 3, No. 12, Dec. 1996.
[21] A. I. Zaye, “A convolution and product theorem for the fractional Fourier,” IEEE Signal Processing Letter, Vol. 5, No. 4, Apr. 1998.
[22] R. Torres, P. Pellat-Finet, Y. Torres, “Fractional convolution, fractional correlation and their translation invariance properties,” Elsevier Signal Processing, Vol. 90, pp. 1976-1984, 2010.
[23] D. Regan, “Human brain electrophysiology : evoked potentials and evoked magnetic fields in science and medicine,” Electroencephalography and Clinical Neurophysiology, July 1989.
[24] K. Singh, N. Singh, P. Kaur, R. Saxena, “Image Compression By Using Fractional Transforms,” 2009 International Conference on Advances in Recent Technologies in Communication and Computing, 2009.
[25] R. Kumar, K. Singh, R. Khanna, “Satellite Image Compression using Fractional Fourier Transform,” International Journal of Computer Applications, Vol. 50, No.3, July 2012.
[26] S. A. Elgamel, C. Clemente, J. J. Soraghan, “Radar Matched Filtering using the Fractional Fourier Transform,” Sensor Signal Processing for Defence (SSPD 2010), Sep. 2010.
[27] I. Djurovic, S. Stankovic, I. Pitas, “Digital watermarking in the fractional Fourier transformation domain,” Journal of Network and Computer Applications, Vol. 24, pp. 167-173, 2001.
[28] S. Liu, L. Yu, B. Zhu, “Optical image encryption by cascaded fractional Fourier transforms with random phase filtering,” Elsevier Optics Communications, Vol. 187, pp. 57-63, 2001.
[29] P. H. Chou, H. T. Chang, “Optical image encryption system based on dyadic phase displacement, toral automorphism, and fractional Fourier transform,” International Conference on Optics and Photonics in Taiwan, Taipei, Taiwan, Dec. 2008.

指導教授

徐國鎧(Kuo-kai Shyu)

審核日期

2014-7-31

推文