VEP-based brain-computer interfaces modulated by Golay complementary series for improving performance
Abstract
BACKGROUND:
The goal of a brain-computer interface (BCI) is to enable communication by pure brain activity without neural and muscle control. However, the practical use of BCIs is limited by low information transfer rate. Recently, code modulation visual evoked potential (c-VEP) based BCIs have exhibited great potential in establishing high-rate communication between the brain and the external world.
OBJECTIVE:
This study aims at exploring a more effective modulation code than the commonly used pseudorandom M sequence for c-VEP based BCIs (c-VEP BCIs) in order to increase the detection accuracy of stimulus targets and the resulting information transfer rate.
METHOD:
Golay complementary sequence pair is used for constructing the modulation code of c-VEP BCIs due to their superior autocorrelation property. The modulation code is created by concatenating a pair of Golay complementary sequences. Sixteen target stimuli are modulated by the Golay code and its time shift versions.
RESULTS:
Through offline analysis on data recorded from seven subjects and online test on five subjects, the Golay code modulated BCI yielded higher detection accuracy and information transfer rate than those achieved by M sequence.
CONCLUSION:
The Golay code modulated BCI demonstrates a high performance compared with the M sequence modulated systems, and it is applicable to persons with motor disabilities.
References
[1] | Wolpaw JR, , Birbaumer N, , McFarland DJ. Pfurtscheller G and Vaughan N. Brain-computer interfaces for communication and control. Clin. Neurophysiol. (2002) ; 113: (6): 767-791. |
[2] | Wolpaw JR, , Birbaumer N, , Heetderks WJ, , McFarland DJ, , Peckham PH, et al. Brain-computer interface technology: A review of the first international meeting. IEEE Trans. Rehabil. Eng. (2000) ; 8: (2): 164-173. |
[3] | Bin G, , Gao X, , Wang Y, , Li Y, , Hong B, , and Gao S. A high speed BCI based on code modulation VEP. Journal of Neural Engineering. (2011) ; 8: (2): 025015. |
[4] | Sutter EE. The visual evoked response as a communication channel. IEEE Trans. Biomed. Eng. (1984) ; 31: (8): 583-583. |
[5] | Sutter EE. The brain response interface: communication through visually-induced electrical brain responses. Journal of Microcomputer Applications. (1992) ; 15: (1): 31-45. |
[6] | Barker HA, and Obidegwu SN. Effects of nonlinearities on the measurement of weighting functions by cross correlation using pseudorandom signals. Proc. IEEE. (1973) ; 120: (10): 1293-1300. |
[7] | Golay MJE. Complementary Series. IRE Transactions on Information Theory. (1961) ; 7: (2): 82-87. |
[8] | Braum V. Golay sequences for identification of linear systems with weak nonlinear distortion. Science, Measurement and Technology. IEE Proceedings. (1998) ; 145: (3): 123-128. |
[9] | Takeuchi Y. An investigation of a spread energy method for medical ultrasound systems. Part one: theory and investigation. Ultrasonics. (1979) ; 17: (4): 175-182. |
[10] | Braun V. Impulse response measurement of a magnetic recording channel using Golay complementary sequences. IEEE Trans. Magrz. (1997) ; 34: (l): 309-316. |
[11] | Shen J, and Ebbini ES. A new coded-excitation ultrasound imaging system - Part I: basic principle. IEEE Transactions on Ultrosonic, Ferroelectrics, and Frequency Control. (1996) ; 43: (1): 131-196. |
[12] | Bin G, , Gao X, , Yan Z, , Hong B, and Gao S. An online multi-channel SSVEP-based brain - computer interface using a canonical correlation analysis method. J. Neural Eng. (2009) ; 6: (4): 978-1007. |