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Article type: Research Article
Authors: Yao, Zhaolina; b | Wang, Yijuna; b; * | Yang, Chenc | Pei, Weihuaa; b | Gao, Xiaorongc | Chen, Hongdaa; b
Affiliations: [a] State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China | [b] University of Chinese Academy of Sciences, Beijing, China | [c] Department of Biomedical Engineering, Tsinghua University, Beijing, China
Correspondence: [*] Corresponding author: Yijun Wang, State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences %****␣ica-26-ica180586_temp.tex␣Line␣50␣**** Beijing 100083, China. E-mail: [email protected].
Abstract: The brain-computer interface (BCI) technology provides a potential tool for communication and control in immersive virtual reality (VR) environments. However, implementing a BCI with current VR platforms remains a challenge due to difficulties in system design and electroencephalogram (EEG) analysis. This study aims to explore the feasibility of a steady-state visual evoked potential (SSVEP)-based BCI for applications in room-scale VR with an HTC VIVE headset. A four-class BCI was designed to simulate a cursor control system. Subjects were instructed to perform a cue-guided target selection task during standing or walking on a treadmill at four different speeds (0, 0.45, 0.89, and 1.34 meters per second (m/s)). During the experiment, two fixing modes of visual stimuli (head-fixed and earth-fixed) were presented to the head-mounted display (HMD). The results from a group of 10 subjects indicated that the system worked well regarding classification accuracy. The BCI performance decreased as the walking speed increased. Interestingly, the earth-fixed condition showed significantly higher performance than the head-fixed condition, showing online and offline information transfer rates (ITRs) corresponding to unsupervised and supervised algorithms above 10 bits/min and 21 bits/min, respectively. These results demonstrated the potential of an SSVEP-based BCI for applications in room-scale mobile VR environments.
Keywords: Brain-computer interface, electroencephalogram, virtual reality, steady-state visual evoked potential
DOI: 10.3233/ICA-180586
Journal: Integrated Computer-Aided Engineering, vol. 26, no. 4, pp. 345-360, 2019
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