A Spectrally-dense Encoding Method for Designing a High-speed SSVEP-BCI with 120 Stimuli

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 30; p. 1
• Main Authors: Chen, Xiaogang, Liu, Bingchuan, Wang, Yijun, Gao, Xiaorong
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Brain; Brain-computer interface (BCI); Computer applications; Effectiveness; electroencephalography (EEG); Encoding; Experiments; Frequency conversion; frequency division multiple access (FDMA); Frequency modulation; Human-computer interface; Implants; Information transfer; joint frequency-phase modulation (JFPM); large number of stimuli; Phase modulation; steady-state visual evoked potential (SSVEP); Target recognition; Task analysis; Training; Visual evoked potentials; Visual stimuli; Visualization
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2022.3208717

The practical functionality of a brain-computer interface (BCI) is critically affected by the number of stimuli, especially for steady-state visual evoked potential based BCI (SSVEP-BCI), which shows promise for the implementation of a multi-target system for real-world applications. Joint frequency-phase modulation (JFPM) is an effective and widely used method in modulating SSVEPs. However, the ability of JFPM to implement an SSVEP-BCI system with a large number of stimuli, e.g., over 100 stimuli, remains unclear. To address this issue, a spectrally-dense JPFM (sJFPM) method is proposed to encode a broad array of stimuli, which modulates the low-and medium-frequency SSVEPs with a frequency interval of 0.1 Hz and triples the number of stimuli in conventional SSVEP-BCI to 120. To validate the effectiveness of the proposed 120-target BCI system, an offline experiment and a subsequent online experiment testing 18 healthy subjects in total were conducted. The offline experiment verified the feasibility of using sJFPM in designing an SSVEP-BCI system with 120 stimuli. Furthermore, the online experiment demonstrated that the proposed system achieved an average performance of 92.47±1.83% in online accuracy and 213.23±6.60 bits/min in online information transfer rate (ITR), where more than 75% of the subjects attained the accuracy above 90% and the ITR above 200 bits/min. This present study demonstrates the effectiveness of sJFPM in elevating the number of stimuli to more than 100 and extends our understanding of encoding a large number of stimuli by means of finer frequency division.