脑机接口竞赛2003——数据集IV：一种基于交叉对称短时距离和判别式滤波分析的单通道脑电图分类算法
BCI Competition 2003--Data set IV: an algorithm based on CSSD and FDA for classifying single-trial EEG.
作者信息
Wang Yijun, Zhang Zhiguang, Li Yong, Gao Xiaorong, Gao Shangkai, Yang Fusheng
机构信息
Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
出版信息
IEEE Trans Biomed Eng. 2004 Jun;51(6):1081-6. doi: 10.1109/TBME.2004.826697.
This paper presents an algorithm for classifying single-trial electroencephalogram (EEG) during the preparation of self-paced tapping. It combines common spatial subspace decomposition with Fisher discriminant analysis to extract features from multichannel EEG. Three features are obtained based on Bereitschaftspotential and event-related desynchronization. Finally, a perceptron neural network is trained as the classifier. This algorithm was applied to the data set (self-paced 1s) of "BCI Competition 2003" with a classification accuracy of 84% on the test set.
本文提出了一种在自定节奏轻敲准备过程中对单次试验脑电图（EEG）进行分类的算法。它将共同空间子空间分解与Fisher判别分析相结合，从多通道EEG中提取特征。基于 Bereitschaftspotential 和事件相关去同步化获得了三个特征。最后，训练了一个感知器神经网络作为分类器。该算法应用于“2003年脑机接口竞赛”的数据集（自定节奏1秒），在测试集上的分类准确率为84%。
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