Multichannel spectral pattern separation - An EEG processing application -
Multichannel spectral pattern separation - An EEG processing application -
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多通道频谱模式分离 - 脑电图处理应用 -
DOI：
10.1109/icassp.2009.4959598
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
A. Ralescu
中科院分区：
文献类型：
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作者：
Tomasz M. Rutkowski;A. Cichocki;Toshihisa Tanaka;D. Mandic;Jianting Cao;A. Ralescu
多通道记录中的信息分离问题在诸如脑机接口（BCI/BMI）的工程应用中是重要的。虽然这个问题并不完全是新的，但将人类的精神状态与所观察到的脑电图（EEG）记录联系起来的工程方法仍处于起步阶段，主要是由于电生理去噪的问题。以EEG形式捕获的电生理信号携带以神经生理成分形式的脑活动，所述神经生理成分通常嵌入在高得多的功率电肌肉活动成分（肌电图- EMG;眼电图- EOG;等）中。在本文中，我们提出了一种方法，以消除肌肉干扰所造成的眼动从脑电听觉实验中记录在一个八通道记录设置。这是通过在希尔伯特域中分析多通道信号内的振荡模式的相关性来实现的。在真实的世界听觉BCI设置中的模拟支持分析。
A problem of information separation in multichannel recordings is important in engineering applications such as brain computer/machine interfaces (BCI/BMI). Whereas this problem is not entirely new, engineering approaches connecting the mental states of humans and the observed electroencephalography (EEG) recordings are still in their infancy, mostly due to problems with electrophysiological denoising. The electrophysiological signals captured in form of the EEG carry brain activity in form of the neurophysiological components which are usually embedded in much higher power electrical muscle activity components (electromyography - EMG; electrooculography - EOG; etc.). In this paper we present an approach to remove muscular interference caused by eye-movements from EEG recorded during auditory experiments in an eight channel recording setting. This is achieved by analyzing the correlation of the oscillatory modes within a multichannel signal in the Hilbert domain. Simulations in a real world auditory BCI setting support the analysis.