摘要
目的通过高频刺激提升基于稳态视觉诱发电位(SSVEP)的脑-机接口(BCI)的用户舒适度,同时结合双频编码,克服高频导致的解码准确率下降问题。方法基于25.5~39.6 Hz频率设计了左右视野和棋盘格视觉刺激的2种60指令双频高频编码范式。共采集了13名受试者的数据,针对SSVEP信号进行频域空域特征分析,并根据频域诱发成分优化滤波器组参数。分别采用滤波器组的扩展典型相关分析(eCCA)、集成任务相关成分分析(eTRCA)以及任务判别模式分析(TDCA)等算法进行SSVEP识别以验证范式可行性。结果左右视野和棋盘格范式均成功诱发了稳定的SSVEP,左右视野基频及其谐波信噪比高,互调成分信噪比较弱,而棋盘格2个刺激频率的互调成分f1+f2的信噪比则明显高于30 Hz以上的二次谐波成分,同时还存在f2?f1成分和2f1?f2成分。结合脑地形图可以看出左右视野的f1和f2响应成分分别位于视野的对侧,而棋盘格则均集中于枕区中央。对于脑地形图振幅和信噪比的偏侧,左右视野刺激频率下PO3和PO4信噪比平均值符合对侧响应特征。5fb?1方法为最优滤波器组设置方法,左右视野TDCA的识别正确率最高,而棋盘格eTRCA和TDCA的识别正确率比较差异没有统计学意义(P>0.05),3种算法的信息传输速率均随数据长度的增加先升高后降低。结论设计的双频高频SSVEP-BCI范式能够较好平衡性能和舒适度,为实用性的大指令集BCI设计方法提供依据。
Objective To improve the users’comfort of steady-state visual evoked potential(SSVEP)-based brain-computer interface(BCI)through high-frequency stimulation and overcome the problem of accuracy decline caused by high frequency by combining dual-frequency encoding.Methods Two dual-frequency high-frequency 60-instruction paradigms based on left and right visual fields and checkerboard stimuli were designed based on the 25.5-39.6 Hz frequency.Thirteen subjects participated in the experiment,and spectrum and spatial characteristics analyses were performed on SSVEP signals.The filter bank parameters were optimized based on the spectrum characteristics.Extended canonical correlation analysis(eCCA),ensemble task-related component analysis(eTRCA),and task-discriminant component analysis(TDCA)were used for SSVEP recognition.Results Stable SSVEP was successfully induced in both the left and right visual fields and the checkerboard grid paradigm.The left and right visual fields had high signal-to-noise ratios for the fundamental frequency and its harmonics and weak signal-to-noise ratios for intermodulation components,whereas the intermodulation components of the 2 stimulus frequencies of the checkerboard grid,f1+f2,had significantly higher signal-to-noise ratios than the second harmonic components above 30 Hz,and there was also a f2−f1 component and a 2f1−f2 component.Combined with brain topography,it can be seen that the f1 and f2 response components of the left and right visual fields are located on opposite sides of the visual field,while the checkerboard grids are both concentrated in the center of the occipital region.Regarding the lateralization of brain topography amplitude and signal-to-noise ratio,the mean values of the PO3 and PO4 signal-to-noise ratios at the stimulation frequency of the left and right visual fields are consistent with the contralateral response characteristics.The 5fb−1 method is the optimal filter set setting method,and the recognition correctness rate of TDCA for the left and right vis
作者
陈小荷
柯余峰
徐伟
明东
Chen Xiaohe;Ke Yufeng;Xu Wei;Ming Dong(Academy of Medical Engineering and Translational Medicine,Tianjin University,Tianjin 300072,China)
出处
《国际生物医学工程杂志》
CAS
2023年第4期288-299,共12页
International Journal of Biomedical Engineering
基金
国家自然科学基金项目(62276184)。
关键词
脑-机接口
中高频稳态视觉诱发电位
双频编码
脑电图
Brain-computer interface
High-frequency steady-state visual evoked potential
Dual-frequency coding
Electroencephalography
