独立成分分析在生物医学信号处理中的应用

Application of independent component analysis in biomedical signals processing

独立成分分析(independentcomponentanalysis熏ICA)已经成功地应用到生物医学信号处理中,并被证明是一种分析生物医学信号的强有力的工具,近年来一直受到国内外学者的广泛关注。本文系统地介绍了独立成分分析在生物医学信号(EEG,MEG,fMRI)处理中的应用,分析了其应用方法,最后简要地探讨了独立成分分析应用到生物医学信号中的优势及存在的一些不足。

Independent component analysis(ICA) has been successfully applied to biomedical signals(electroencephalograph,EEG; magnetoencephalograph,MEG; functional magnetic reasonance imaging,fMRI)processing,and proved to be a strong tool for biomedical signals processing. This paper systematically introduced applications of ICA to biomedical signals processing concerned by the domestic and international schaloars in recent years,points out the advantages and insufficiencies.