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针对中低频稳态视觉诱发电位(steady-state visual evoked potential,SSVEP)易于导致视觉疲劳的缺点以及现有高频范式对视觉激励载体要求较高的不足,通过应用相位编码方法,基于普通液晶显示器搭建了面向仿人机器人导航的高频SSVEP用户界面;同时针对高频SSVEP较难识别的特点,提出一种新的模糊分类方法来提高脑电信号解码效率.仿人机器人导航实验表明,基于中频SSVEP范式的脑—机器人导航系统的准确率、碰撞次数、操作频率分别为92.44%、2.14次、11.23次/min,而且极易使受试感到不适.而高频SSVEP的应用缓解了视觉疲劳,将导航系统的准确率、碰撞次数、操作频率分别提升至93.31%、1.89次与12.05次/min.
In view of the shortcomings of low-frequency steady-state visual evoked potential (SSVEP) that easily lead to visual fatigue and the existing high-frequency paradigm demanding for the visual excitation carrier, by applying the phase encoding method and based on ordinary liquid crystal display A high-frequency SSVEP user interface oriented to humanoid robot navigation is constructed. At the same time, a new fuzzy classification method is proposed to improve the efficiency of EEG signal decoding based on the characteristics that SSVEP is more difficult to identify.Finally, human- SSVEP paradigm of brain-robot navigation system accuracy, collision frequency, operating frequency were 92.44%, 2.14 times, 11.23 times / min, and easily make the test feel uncomfortable.However, the application of high-frequency SSVEP alleviate the visual fatigue, The navigation system accuracy, collision frequency, operating frequency were raised to 93.31%, 1.89 times and 12.05 times / min.