Yufeng Ke1, Pengxiao Liu, Xingwei An, Xizi Song, Dong Ming. 1. Academy of Medical Engineering and Translational Medicine, Tianjin International Joint Research Centre for Neural Engineering, and Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.
Abstract
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.
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.