Optimizing Stimulus Frequency Ranges for Building a High-Rate High Frequency SSVEP-BCI

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 31; pp. 1277 - 1286
• Main Authors: Chen, Xiaogang, Liu, Bingchuan, Wang, Yijun, Cui, Hongyan, Dong, Jianwei, Ma, Ruijuan, Li, Ning, Gao, Xiaorong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: BCI; Calibration; Electrodes; Electroencephalography; Encoding; Frequency modulation; Frequency ranges; High frequencies; high-frequency visual stimulation; Human-computer interface; Information transfer; Interfaces; Signal to noise ratio; SSVEP; Task analysis; Visual evoked potentials; Visual stimuli; Visualization
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2023.3243786

The brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) have been extensively explored due to their advantages in terms of high communication speed and smaller calibration time. The visual stimuli in the low- and medium-frequency ranges are adopted in most of the existing studies for eliciting SSVEPs. However, there is a need to further improve the comfort of these systems. The high-frequency visual stimuli have been used to build BCI systems and are generally considered to significantly improve the visual comfort, but their performance is relatively low. The distinguishability of 16-class SSVEPs encoded by the three frequency ranges, i.e., 31-34.75 Hz with an interval of 0.25 Hz, 31-38.5 Hz with an interval of 0.5 Hz, 31-46 Hz with an interval of 1 Hz, is explored in this study. We compare classification accuracy and information transfer rate (ITR) of the corresponding BCI system. According to the optimized frequency range, this study builds an online 16-target high frequency SSVEP-BCI and verifies the feasibility of the proposed system based on 21 healthy subjects. The BCI based on visual stimuli with the narrowest frequency range, i.e., 31-34.5 Hz, have the highest ITR. Therefore, the narrowest frequency range is adopted to build an online BCI system. An averaged ITR obtained from the online experiment is 153.79 ±6.39 bits/min. These findings contribute to the development of more efficient and comfortable SSVEP-based BCIs.