多頻相位編碼之閃光視覺誘發電位驅動大腦人機介面

Implementation of a high-performance steady-state visual evoked potential (SSVEP)-based brain computer interface using frequency and phase encoded flash lights

謝竣傑(Jyun-jie Sie)

指導教授 ： 李柏磊

國立中央大學/資訊電機學院/電機工程學系/碩士(2007年)

摘要

本研究開發利用多頻相位編碼之閃光視覺誘發電位(Visual Evoked Potential, VEP)控制的大腦人機界面(Brain Computer Interface, BCI)。我們對空間中不同位置的閃光刺激進行不同頻率與不同相位的編碼，藉由使用者對其視野中央的光刺激會有最大對應視覺誘發電位的特性，我們可以藉由偵測使用者腦波的時序，判斷目前使用者正在注視的光源是哪一個，進一步讓使用者可以利用注視不同的光源，達到按鍵或指令輸入的目的。本系統結合了穩態視覺誘發電位(Steady-State Visual Evoked Potential, SSVEP)與閃爍視覺誘發電位(Flash Visual Evoked Potential, FVEP)的優點，改善了傳統穩態視覺誘發電位腦波人機界面系統(SSVEP-based BCI)通道數不足與閃爍視覺誘發電位腦波人機界面系統(FVEP-based BCI)低傳輸率的缺點。本大腦人機界面目前已經可以讓使用者進行八個按鍵的輸入，並已經可以達到0.52 sec/command的傳輸速度與100%的準確率。

關鍵字

多頻相位編碼之閃光視覺誘發電位 ； 大腦人機界面 ； 腦電波

並列摘要

The present study proposes a new visual evoked potential (VEP)-based brain computer interface (BCI). Users gaze at different spatially separated flash channels (FCs) in order to induce visual evoked signals that have temporal sequences corresponding to the gazed FCs, so that the gazed FC can be recognized and the command mapping to the gazed FC can be sent out to achieve control purposes. To achieve distinct flickering sequences among different FCs, we utilized different frequencies and phases to encode the flashing sequences of different FCs. The proposed system provides the high flexibility in expansion of FC number and high information transfer rate (ITR) which are superior to the traditional SSVEP-based and FVEP-based BCIs. In this thesis, we have built an eight-FC system. The command transfer rate and detected accuracy are 0.52 sec/command and 100%, respectively.

並列關鍵字

brain-computer interface (BCI) ； frequency and phase encoded flash lights ； electroencephalography (EEG)

參考文獻

[4] S.P. Levine, J.E. Huggins, S.L. BeMent, R.K. Kushwaha, L.A. Schuh, M.M. Rohde, E.A. Passaro, D.A. Ross, K.V. Elisevich, and B.J. Smith, "A direct brain interface based on event-related potentials," IEEE Trans. Rehabil. Eng., vol. 8, pp. 180-185, 2000.

[1] J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, and T.M. Vaughan, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, pp. 767-791, 2002.

[2] T.M. Vaughan, W.J. Heetderks, L.J. Trejo, W.Z. Rymer, M. Weinrich, M.M. Moore, A.Kubler, B.H. Dobkin, N. Birbaumer, E. Donchin, E.W. Wolpaw, and J.R. Wolpaw, "Brain-computer interface technology: A review of the second international meeting," IEEE Trans. Rehabil. Eng., vol. 11, pp. 94-109, 2003.

[3] B. Blankertz, K.R. Müller, G. Curio, T.M. Vaughan, G. Schalk, J.R. Wolpaw, A. Schloegl, C. Neuper, G. Pfurtscheller, T. Hinterberger, M. Schroeder, and N. Birbaumer, "The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials," IEEE Trans. Biomed. Eng., vol. 51, pp. 1044-1051, 2004.

[5] G. Pfurtscheller et al., "Current trends in Graz brain-computer interface (BCI) research," IEEE Trans. Rehab. Eng., vol. 8, pp. 216-219, 2000.