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发表刊物：35th Annual International Conference of the IEEE EMBS

摘要：An automatic artifact removal method of magnetoencephalogram (MEG) was presented in this paper. The method proposed is based on independent components analysis (ICA) and support vector machine (SVM). However, different from the previous studies, in this paper we consider two factors which would influence the performance. First, the imbalance factor of independent components (ICs) of MEG is handled by weighted SVM. Second, instead of simply setting a fixed weight to each class, a re-weighting scheme is used for the preservation of useful MEG ICs. Experimental results on manually marked MEG dataset showed that the method proposed could correctly distinguish the artifacts from the MEG ICs. Meanwhile, 99.72%+-0.67 of MEG ICs were preserved. The classification accuracy was 97.91%+-1.39. In addition, it was found that this method was not sensitive to individual differences. The cross validation (leave-one-subject-out) results showed an averaged accuracy of 97.41%+-2.14.

论文类型：会议论文

是否译文：否

发表时间：2013-07-03

第一作者：段放

合写作者：Montri Phothisonothai,Mitsuru Kikuchi,Yuko Yoshimura,Yoshio Minabe,Kastumi Watanabe,Kazuyuki Aihara