脑机接口竞赛2003——数据集IIb：基于独立成分分析的子空间投影增强P300波检测在脑机接口应用中的研究
BCI Competition 2003--Data set IIb: enhancing P300 wave detection using ICA-based subspace projections for BCI applications.
作者信息
Xu Neng, Gao Xiaorong, Hong Bo, Miao Xiaobo, 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):1067-72. doi: 10.1109/TBME.2004.826699.
An algorithm based on independent component analysis (ICA) is introduced for P300 detection. After ICA decomposition, P300-related independent components are selected according to the a priori knowledge of P300 spatio-temporal pattern, and clear P300 peak is reconstructed by back projection of ICA. Applied to the dataset IIb of BCI Competition 2003, the algorithm achieved an accuracy of 100% in P300 detection within five repetitions.
本文介绍了一种基于独立成分分析（ICA）的P300检测算法。在ICA分解之后，根据P300时空模式的先验知识选择与P300相关的独立成分，并通过ICA的反向投影重建清晰的P300峰值。将该算法应用于2003年脑机接口竞赛的数据集IIb，在五次重复实验中，该算法在P300检测中的准确率达到了100%。
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