Motor imagery task discrimination using wide-band frequency spectra with Slepian tapers.
Motor imagery task discrimination using wide-band frequency spectra with Slepian tapers.
复制标题
使用具有 Slepian 锥度的宽带频谱进行运动想象任务辨别。
DOI：
10.1109/iembs.2010.5627899
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Geronimo,A
中科院分区：
文献类型：
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作者：
Kamrunnahar,M;Geronimo,A
在这里，我们研究了宽带频谱（WBFS）功能，使用多锥度（MT）频谱分析在运动想象的脑机接口的应用。我们获得了运动想象任务相关的人头皮脑电图（EEG）信号的左与右手运动使用3对不同的视觉箭头线索。使用朴素贝叶斯分类器，使用WBFS特征和来自中央+顶叶和仅中央电极位置的EEG信号的常用Mu-Beta谱特征，进行左与右运动图像区分。任务判别精度结果表明，WBFS功能使用MT光谱分析提供了显着更好的性能（95%的置信水平）比使用常用的Mu-Beta光谱功能。使用中央+顶叶电极信号的歧视的准确性显着改善相比，使用中央只有信号的准确性，这意味着感官信息增强任务的歧视显着。
We here studied the efficacy of wide-band frequency spectra (WBFS) features using multi-taper (MT) spectral analysis in application to motor imagery based Brain Computer Interfaces. We acquired motor imagery task related human scalp electroencephalography (EEG) signals for left vs. right hand movements using 3 different pairs of visual arrow cues. Left vs. right movement imagery discrimination was conducted using a Naïve Bayesian classifier using WBFS features and commonly used Mu-Beta spectral features for EEG signals from central+parietal and central only electrode positions. Task discrimination accuracy results showed that WBFS features using MT spectral analysis provided significantly better performance (with a 95% confidence level) than that of using Mu-Beta spectral features commonly used. The use of central+parietal electrode signals improved discrimination accuracy significantly when compared to the accuracy using the central only signals, implying that sensory information enhanced task discrimination significantly.