{"title":"EEG brain map reconstruction using blind source separation","authors":"S. Sanei, A. R. Leyman","doi":"10.1109/SSP.2001.955265","DOIUrl":null,"url":null,"abstract":"EEG-based brain maps are very useful in anatomical, functional and pathological diagnosis. These images are projections of the energy of the signals in four different frequency bands. Joint approximate diagonalization of eigenmatrices (JADE) is used as an effective tool in the deconvolution of EEG signals prior to spectrum estimation. The algorithm also, restores the noise from the signal as a result of higher order statistics (HOS) estimation. The spectrum is estimated using autoregressive (AR) modelling and pseudo-hot colours are used to represent brain activities. The results show a great enhancement in diagnostic features in the reconstructed images. The overall system also enables real-time reconstruction of the images for patient monitoring purposes.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"97 1","pages":"233-236"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"信号处理","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/SSP.2001.955265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
EEG-based brain maps are very useful in anatomical, functional and pathological diagnosis. These images are projections of the energy of the signals in four different frequency bands. Joint approximate diagonalization of eigenmatrices (JADE) is used as an effective tool in the deconvolution of EEG signals prior to spectrum estimation. The algorithm also, restores the noise from the signal as a result of higher order statistics (HOS) estimation. The spectrum is estimated using autoregressive (AR) modelling and pseudo-hot colours are used to represent brain activities. The results show a great enhancement in diagnostic features in the reconstructed images. The overall system also enables real-time reconstruction of the images for patient monitoring purposes.
期刊介绍：
Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.
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