计算机工程与应用 ›› 2021, Vol. 57 ›› Issue (8): 153-159.DOI: 10.3778/j.issn.1002-8331.2001-0189

• 模式识别与人工智能 • 上一篇    下一篇

新颖的稳态视觉诱发电位脑机接口系统

乔敏,张德雨,刘思宇,闫天翼,相洁   

  1. 1.太原理工大学 信息与计算机学院,太原 030600
    2.北京理工大学 机电学院,北京 100081
    3.北京理工大学 生命学院,北京 100081
  • 出版日期:2021-04-15 发布日期:2021-04-23

Novel Brain-Computer Interface System Based on Steady-State Visual Evoked Potential

QIAO Min, ZHANG Deyu, LIU Siyu, YAN Tianyi, XIANG Jie   

  1. 1.College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
    2.School of Electromechanics, Beijing Institute of Technology, Beijing 100081, China
    3.School of Life Science, Beijing Institute of Technology, Beijing 100081, China
  • Online:2021-04-15 Published:2021-04-23

摘要:

传统的稳态视觉诱发电位(SSVEP)脑机接口系统无法与现实世界进行交互,长时间单调的光闪烁刺激容易导致视觉疲劳,影响识别精度。为了增强人与机器的交互以及对环境的感知,设计了增强现实(AR)和SSVEP结合的范式,在真实环境下对物体进行识别与追踪,并将闪烁块对物体进行标记,采用滤波器组典型相关分析(FBCCA)方法对脑电信号进行处理。结果表明,系统的控制信号传输速度达到50.69 bit/min,FBCCA的识别正确率为99.68%,能够在1 s内对4个目标中的意图目标进行有效区分。研究表明,基于SSVEP和增强现实的脑机接口系统更适合于复杂的现实环境。

关键词: 脑机接口, 增强现实, 稳态视觉诱发电位

Abstract:

The traditional Steady-State Visual Evoked Potential(SSVEP) brain-computer interface system cannot interact with the real world, and the long time monotonous light flashing stimulation is easy to cause visual fatigue and affect the recognition accuracy. In order to enhance the interaction between humans and machines and the perception of the environment, this study designs a paradigm combining Augmented Reality(AR) and SSVEP to identify and track objects in the real environment, marking objects with flashing blocks, and processing EEG signals using the Filter Bank Canonical Correlation Analysis(FBCCA) method. The results show that the control signal transmission speed of the system reaches 50.69 bit/min, the recognition accuracy of FBCCA is 99.68%, and the intended targets can be distinguished within 1 s. Studies have shown that brain computer interface systems based on SSVEP and augmented reality are more suitable for complex real-world environments.

Key words: brain-computer interface, augmented reality, steady-state visual evoked potential