生物医学工程学杂志

生物医学工程学杂志

错误相关负电位单次检测技术研究

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当个体在感知发生错误时,会在头皮额中央区产生错误相关负电位(ERN)。ERN 信噪比低、个体差异大,单次检测 ERN 比较困难。本文采用 ERN 大脑活动模式图和离线识别正确率的方法优选脑电信号通道,进一步基于 ERN 离线识别正确率对时间段进行优选,然后基于小波变换对 ERN 的低频时域特征与高频时—频域特征进行了分析,在此基础上提出了 ERN 的单次检测算法。最后,通过使用优选出的 6 个通道反馈刺激后 200~600 ms 的脑电数据,提取 0~3.9 Hz 频段的降采样点特征和 3.9~15.6 Hz 频段的能量、方差特征,对 ERN 和非 ERN 进行单次识别,在 10 名受试者中实现了 72.0% ± 9.6% 的识别正确率。本文的研究结果有助于错误指令实时纠正技术在脑—机接口在线系统中的应用。

Error related negativity (ERN) is generated in frontal and central cortical regions when individuals perceive errors. Because ERN has low signal-to-noise ratio and large individual difference, it is difficult for single trial ERN recognition. In current study, the optimized electroencephalograph (EEG) channels were selected based on the brain topography of ERN activity and ERN offline recognition rate, and the optimized EEG time segments were selected based on the ERN offline recognition rate, then the low frequency time domain and high frequency time-frequency domain features were analyzed based on wavelet transform, after which the ERN single detection algorithm was proposed based on the above procedures. Finally, we achieved average recognition rate of 72.0% ± 9.6% in 10 subjects by using the sample points feature in 0~3.9 Hz and the power and variance features in 3.9~15.6 Hz from the EEG segments of 200~600 ms on the selected 6 channels. Our work has the potential to help the error command real-time correction technique in the application of online brain-computer interface system.

关键词: 错误相关负电位; 脑—机接口; 小波变换; 时频域特征; 单次检测

Key words: error related negativity; brain-computer interface; wavelet transform; time-frequency domain features; single trial recognition

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