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A novel brain source reconstruction using a multivariate mode decomposition
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DOI：10.1088/1741-2552/acdffe.png)
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Objective. Brain source reconstruction through electroencephalogram is a challenging issue in brain research with possible applications in cognitive science as well as brain damage and dysfunction recognition. Its goal is to estimate the location of each source in the brain along with the signal being produced. Approach. In this paper, by assuming a small number of band limited sources, we propose a novel method for the problem by using successive multivariate variational mode decomposition (SMVMD). Our new method can be considered as a blind source estimation method, which means that it is capable of extracting the source signal without the knowledge of the location of the source or its lead field vector. In addition, the source location can be determined through comparing the mixing vector found in SMVMD and the lead filed vectors of the entire brain. Main results. The simulations verify that our method leads to performance improvement in comparison to the well-known localization and source signal estimation techniques such as MUltiple SIgnal Calssification (MUSIC), recursively applied and projected MUSIC, dipole fitting method, MV beamformer, and standardized low-resolution brain electromagnetic tomography. Significance. The proposed method enjoys low computational complexity. Moreover, our investigations on some experimental epileptic data confirm its superiority over the MUSIC method in the aspect of localization accuracy.
Keyword:
brain signal reconstruction
EEG source localization
successive multivariate mode decomposition
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3.8
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被引数:
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