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目的 实现脑电信号的采取和处理,以及准确的解调基于编码刺激的稳态视觉诱发电位(steadystate visual evoked potential,SSVEP)信号.方法 采用数字通信中的频移键控(frequency shift keying,FSK)编码策略对SSVEP刺激频率进行编码;用4行4列的LED阵列组成刺激器,并准确提取脑电信号中的SSVEP信号;使用经验模态分解(empirical mode decomposition,EMD)对提取到的SSVEP信号做预处理提高采集信号的信噪比,并使用FSK传统解调算法——非相干解调来实现对编码频率的解调.结果 参与实验的10名志愿者,在FSK-SSVEP系统中的解调平均正确率高于90％.结论 基于EMD和非相干解调算法系统可实现高正确率的解调,并且使用FSK编码机制可解决传统SSVEP-BCI系统中刺激频率受到刺激器刷新率的限制,而缺乏可用的调制频率的问题.“,”Objective To realize the EEG signal acquisition and processing,and the accurate demodulation of the steady-state visual evoked potential (SSVEP) signal based on coded stimulus.Methods The frequency shift keying (FSK) coding strategy in digital communication was adopted to encode the SSVEP stimulation frequency.The 4 rows and 4 columns LED arrays were used in the stimulator and the SSVEP signal in the EEG signal was accurately extracted.The empirical mode decomposition (EMD) was applied to preprocess the extracted SSVEP signal to improve the signal-to-noise ratio of the acquired signal.With the traditional FSK demodulation algorithm,the non-coherent demodulation,was used to realize the frequency decoding.Results The average accurate rate of demodulation in the FSK-SSVEP system was over 90％ in 10 volunteers participant in the experiment.Conclusion The system based on EMD and non-coherent demodulation algorithm could achieve high accurate rate of demodulation;and the FSK encoding mechanism could solve the problem that the stimulation frequency of the traditional SSVEP-based brain-computer interface (SSVEP-BCI) system is limited by the stimulator refresh rate and the available modulation frequency is lacking.