An online SSVEP-BCI system in an optical see-through augmented reality environment

被引:62
|
作者
Ke, Yufeng [1 ,2 ]
Liu, Pengxiao [1 ,2 ]
An, Xingwei [1 ,2 ]
Song, Xizi [1 ,2 ]
Ming, Dong [1 ,2 ,3 ]
机构
[1] Tianjin Univ, Acad Med Engn & Translat Med, Tianjin Int Joint Res Ctr Neural Engn, Tianjin 300072, Peoples R China
[2] Tianjin Univ, Tianjin Key Lab Brain Sci & Neural Engn, Tianjin 300072, Peoples R China
[3] Tianjin Univ, Dept Biomed Engn, Coll Precis Instrument & Optoelect Engn, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
brain-computer interface; augmented reality; electroencephalogram; steady-state visual evoked potential; optical see-through; BRAIN-COMPUTER INTERFACE; ATTENTION;
D O I
10.1088/1741-2552/ab4dc6
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective. This study aimed to design and evaluate a high-speed online steady-state visually evoked potential (SSVEP)-based brain-computer interface (BCI) in an optical see-through (OST) augmented reality (AR) environment. Approach. An eight-class BCI was designed in an OST-AR headset which is wearable and allows users to see the user interface of the BCI and the device to be controlled in the same view field via the OST head-mounted display. The accuracies, information transfer rates (ITRs), and SSVEP signal characteristics of the AR-BCI were evaluated and compared with a computer screen-based BCI implemented with a laptop in offline and online cue-guided tasks. Then, the performance of the AR-BCI was evaluated in an online robotic arm control task. Main results. The offline results obtained during the cue-guided task performed with the AR-BCI showed maximum averaged ITRs of 65.50 +/- 9.86 bits min(-1) according to the extended canonical correlation analysis-based target identification method. The online cue-guided task achieved averaged ITRs of 65.03 +/- 11.40 bits min(-1). The online robotic arm control task achieved averaged ITRs of 45.57 +/- 7.40 bits min(-1). Compared with the screen-based BCI, some limitations of the AR environment impaired BCI performance and the quality of SSVEP signals. Significance. The results showed the potential for providing a high-performance brain-control interaction method by combining AR and BCI. This study could provide methodological guidelines for developing more wearable BCIs in OST-AR environments and will also encourage more interesting applications involving BCIs and AR techniques.
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收藏
页数:17
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