{"title":"基于EMD和OMP的单通道脑电记录眨眼伪影自动校正","authors":"N. Mourad, R. Niazy","doi":"10.5281/ZENODO.43591","DOIUrl":null,"url":null,"abstract":"In this paper we propose a new technique for automatic correction of eye blink artifact in single channel EEG recording. The proposed technique consists of three steps. In the first two steps a dictionary matrix and a reference signal to the eye blink artifact are constructed from the recorded data, respectively. In the proposed technique we suggest building the dictionary matrix using empirical mode decomposition (EMD). In the last step, orthogonal matching pursuit (OMP) is utilized to find the minimum number of columns of the constructed dictionary matrix that fit the reference signal. Simulation results on real EEG data show that the proposed technique outperforms some of the existing single channel blind source separation techniques.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automatic correction of eye blink artifact in single channel EEG recording using EMD and OMP\",\"authors\":\"N. Mourad, R. Niazy\",\"doi\":\"10.5281/ZENODO.43591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose a new technique for automatic correction of eye blink artifact in single channel EEG recording. The proposed technique consists of three steps. In the first two steps a dictionary matrix and a reference signal to the eye blink artifact are constructed from the recorded data, respectively. In the proposed technique we suggest building the dictionary matrix using empirical mode decomposition (EMD). In the last step, orthogonal matching pursuit (OMP) is utilized to find the minimum number of columns of the constructed dictionary matrix that fit the reference signal. Simulation results on real EEG data show that the proposed technique outperforms some of the existing single channel blind source separation techniques.\",\"PeriodicalId\":400766,\"journal\":{\"name\":\"21st European Signal Processing Conference (EUSIPCO 2013)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"21st European Signal Processing Conference (EUSIPCO 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.43591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st European Signal Processing Conference (EUSIPCO 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.43591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic correction of eye blink artifact in single channel EEG recording using EMD and OMP
In this paper we propose a new technique for automatic correction of eye blink artifact in single channel EEG recording. The proposed technique consists of three steps. In the first two steps a dictionary matrix and a reference signal to the eye blink artifact are constructed from the recorded data, respectively. In the proposed technique we suggest building the dictionary matrix using empirical mode decomposition (EMD). In the last step, orthogonal matching pursuit (OMP) is utilized to find the minimum number of columns of the constructed dictionary matrix that fit the reference signal. Simulation results on real EEG data show that the proposed technique outperforms some of the existing single channel blind source separation techniques.