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

Authors :
Xiaogang Chen
Bingchuan Liu
Yijun Wang
Hongyan Cui
Jianwei Dong
Ruijuan Ma
Ning Li
Xiaorong Gao
Source :
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 1277-1286 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

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.

Details

Language :
English
ISSN :
15580210
Volume :
31
Database :
Directory of Open Access Journals
Journal :
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.1bff598ff265480a8ca412a26998509a
Document Type :
article
Full Text :
https://doi.org/10.1109/TNSRE.2023.3243786