Using non-negative matrix fact factorization to extract attention-related EEG features
M-Y Liu, J Wang, Zheng Cx, Ning Yan · Acta Biophysica Sinica · 2006
The fundamental of non-negative matrix factorization algorithm was introduced. It is used to extract EEG power spectrum feature. Artificial neural network is employed as classifier. Three level attention mental tasks are designed to test the method. Ten subjects attended the experiment. The classification accuracies indicate that the NMF technique is a powerful feature extractor in high-dimensional feature space. The average classification accuracy of ten subjects achieves 88%, it is higher obviously than that of principal component analysis and direct method.