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A brain controlled wheelchair based on common spatial pattern

机译：基于常见空间模式的脑控制轮椅

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This paper was proposed for the feature extraction problem in Brain Computer Interface (BCI) which was based on the motor imagery. Common Spatial Pattern (CSP) was used to extract useful features from the Electroencephalograph (EEG) signals. Firstly, a preprocessing step was applied to remove noises. Secondly, CSP was used to analyze with EEG signals. Support Vector Machine (SVM) was investigated to classify motor imagery state. The EEG signals of motor imagery provided by dataset I of 2004 BCI Competition III were used for the validation. The results showed that the algorithm can extract the obvious characteristics efficiently. Finally, the proposed method was used in a wheelchair application. Experimental results showed that the proposed approach was promising for implementing human-computer interaction, especially for EEG-based brain controlled wheelchair.
机译：本文提出了基于电动机图像的脑电脑界面（BCI）中的特征提取问题。常见的空间模式（CSP）用于从脑电图（EEG）信号中提取有用的特征。首先，施加预处理步骤以去除噪声。其次，CSP用于分析EEG信号。调查支持向量机（SVM）以分类电机图像状态。 2004年BCI竞赛III的数据集I提供的电机图像的EEG信号用于验证。结果表明，该算法可以有效地提取明显的特征。最后，所提出的方法用于轮椅应用。实验结果表明，该拟议的方法是对实施人机相互作用的承诺，特别是对于基于EEG的脑控制轮椅。

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