综合频率响应特征和权重系数的自适应脑机接口技术

Research on the adaptive brain computer interface technology of synthesizing frequency response characteristics and weight coefficients

针对稳态视觉诱发电位(SSVEP)响应个体差异性较大和不同电极通道采集脑电信号质量具有差别的问题,提出了综合频率响应特征和权重系数的自适应方法,并进行了实验验证。首先,4名被试者进行了3次SSVEP扫频实验,得到大脑枕区8个电极的SSVEP幅频特性响应通频带;其次,根据电极通道的平均信噪比,求出各电极的权重系数,进而得到被试者的个体幅频特性响应通频带;最后,为避免使用低频闪烁引起的强烈视觉疲劳,选择个体幅频特性响应通频带的中频段(15~30 Hz)作为刺激频率进行脑机接口实验。实验结果表明,所提出的自适应稳态视觉诱发脑机接口在识别时间为3 s时,具有较高的准确率(平均为97.09%)和信息传输率(平均为100.26 bits/min),且有效减轻了视觉疲劳,研究结果为设计基于个体差异特点的脑机接口提供了新的思路。

There are significant individual differences of steady-state visual evoked potential(SSVEP)responses and the different quality of EEG signals collected by different electrode channels.To solve these problems,an adaptive method of synthesizing frequency response characteristics and weight coefficient is proposed and verified by experiments.First,four subjects perform three SSVEP frequency sweep experiments.SSVEP amplitude-frequency characteristic response passband of eight electrodes in the cerebral occipital region is achieved.Secondly,according to the average signal-to-noise ratio of the electrode channels,the weight coefficient of each electrode is received.Then,the subject′s amplitude-frequency characteristic response passband is obtained.Finally,to avoid the intense visual fatigue caused by low-frequency flicker,the mid-band(15~30 Hz)of the individual′s amplitude-frequency characteristic response passband is selected as the stimulation frequency for brain-computer interface experiments.Experimental results show that the proposed adaptive steady-state visual evoked brain-computer interface has high accuracy(97.09%on average)and information transmission rate(100.26 bits/min on average)when the recognition time is 3 s.The visual fatigue is effectively reduced.Research results provide new ideas for the design of a BCI based on individual differences.