DocumentCode :
3745158
Title :
Stimuli with opponent colors and higher bit rate enable higher accuracy for C-VEP BCI
Author :
Hooman Nezamfar;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus
Author_Institution :
Cognitive Systems Laboratory, ECE Department, Northeastern University, Boston, MA 02115, USA
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
Steady state visual evoked potentials are widely exploited in EEG-based BCI systems. Frequency and code based flickering stimuli are the two major methods used to induce SSVEP responses. Considering the tiring effect of flashing icons in the long run, the less noticeable the flashes become, the more tolerable they will be. Based on the user ratings, who experienced both, code and frequency based stimulation, the code based method is less tiring. Hence, we used our SSVEP based BCI system in the code-based mode for this study. Among several aspects of stimuli affecting the system performance and user experience, for this study, we considered color, bit presentation rate and the control bit sequence length as three significant factors. Our main goal is to achieve more pleasant stimuli, while maintaining a high performance. Although, these factors seldom coincide, but, our findings showed that it is possible to find an almost optimum point of operation. In this study, a battery of calibration sessions with three different opponent color pairs of black and white, red and green and blue and yellow, three bit presentation rates of 30, 60 and 110 bps and three control bit sequence lengths of 31, 63 and 127 bits were performed. Our findings are suggestive of a performance increase using opponent colorful pairs as opposed to black and white, with the red-green color pair exceeding the performance of others. Consistently, among all the individuals participating in the study, one second of EEG evidence seems to be adequate to maximize the classification accuracy. This translates to {60 bps , 63 bits} and {110 bps, 127 bits} pairs of bit presentation rate and m-sequence length being the best performers. With a slight decrease in classification performance, half a second of EEG data could be considered when speed is of concern.
Keywords :
"Color","Electroencephalography","Visualization","Image color analysis","Calibration","Frequency modulation","Bit rate"
Publisher :
ieee
Conference_Titel :
Signal Processing in Medicine and Biology Symposium (SPMB), 2015 IEEE
Type :
conf
DOI :
10.1109/SPMB.2015.7405476
Filename :
7405476
Link To Document :
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