综合频率响应特征和权重系数的自适应脑机接口技术

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.