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首页> 外文会议>2011 7th International Conference on Emerging Technologies >Optimizing Common Spatial Pattern and feature extraction algorithm for Brain Computer Interface
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Optimizing Common Spatial Pattern and feature extraction algorithm for Brain Computer Interface

机译：脑计算机接口的公共空间格局优化和特征提取算法

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Brain Computer Interface is the communication channel between the brain and the computer for recording of electrical activity along the scalp produced by the firing of neurons within the brain. The brain signals which are also known as Electroencephalography (EEG) can be used to direct and control some external activity. This work reports a methodology for acquisition and detection and of EEG signals, and extraction of useful information in order to differentiate the signals related to particular type of movement. A modified Common Spatial Pattern (CSP) algorithm has been used at preprocessing stage. Logarithmic transform along with the information theoretic feature extraction has also been used for feature extraction. KNN, SVM and Artificial Neural Networks are employed for classification. The proposed methodology is tested on publically available data sets and the results are found to be comparable with the published approaches.
机译：脑计算机接口是大脑与计算机之间的通信通道，用于记录由大脑内神经元发射所产生的沿头皮的电活动。脑信号，也称为脑电图（EEG），可用于指导和控制某些外部活动。这项工作报告了一种方法，用于获取和检测脑电信号，以及提取有用的信息，以区分与特定类型的运动有关的信号。在预处理阶段使用了一种改进的公共空间模式（CSP）算法。对数变换以及信息理论特征提取也已用于特征提取。使用KNN，SVM和人工神经网络进行分类。在公开可用的数据集上对所提出的方法进行了测试，发现结果与已发布的方法具有可比性。

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