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dc.contributor.authorMoctezuma, Luis Alfredo
dc.contributor.authorMolinas Cabrera, Maria Marta
dc.date.accessioned2019-03-22T13:35:37Z
dc.date.available2019-03-22T13:35:37Z
dc.date.created2019-01-16T15:52:37Z
dc.date.issued2018
dc.identifier.isbn978-3-030-05586-8
dc.identifier.urihttp://hdl.handle.net/11250/2591358
dc.description.abstractWhen brain activity ions, the potential for human capacities augmentation is promising. In this paper, EMD is used to decompose EEG signals during Imagined Speech in order to use it as a biometric marker for creating a Biometric Recognition System. For each EEG channel, the most relevant Intrinsic Mode Functions (IMFs) are decided based on the Minkowski distance, and for each IMF 4 features are computed: Instantaneous and Teager energy distribution and Higuchi and Petrosian Fractal Dimension. To test the proposed method, a dataset with 20 Subjects who imagined 30 repetitions of 5 words in Spanish, is used. Four classifiers are used for this task - random forest, SVM, naive Bayes, and k-NN - and their performances are compared. The accuracy obtained (up to 0.92 using Linear SVM) after 10-folds cross-validation suggest that the proposed method based on EMD can be valuable for creating EEG-based biometrics of imagined speech for Subject identification.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.relation.ispartofBrain Informatics. BI 2018. Lecture Notes in Computer Science
dc.titleEEG-based Subjects Identification based on Biometrics of Imagined Speech using EMDnb_NO
dc.typeChapternb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber458-467nb_NO
dc.identifier.doi10.1007/978-3-030-05587-5_43
dc.identifier.cristin1658607
dc.relation.projectNorges teknisk-naturvitenskapelige universitet: 81771026nb_NO
dc.description.localcodeThis is a post-peer-review, pre-copyedit version of an article published in [Lecture Notes in Computer Science] Locked until 7.12.2019 due to copyright restrictions. The final authenticated version is available online at:https://doi.org/10.1007/978-3-030-05587-5_43nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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