SVD-based on-line exercise ECG signal orthogonalization

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buir.contributor.authorKöymen, Hayrettin
dc.citation.epage321en_US
dc.citation.issueNumber3en_US
dc.citation.spage311en_US
dc.citation.volumeNumber46en_US
dc.contributor.authorAcar, B.en_US
dc.contributor.authorKöymen, Hayrettinen_US
dc.date.accessioned2016-02-08T10:41:50Z
dc.date.available2016-02-08T10:41:50Z
dc.date.issued1999-03en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractAn orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J- point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.An orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J-point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:41:50Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1999en
dc.identifier.doi10.1109/10.748984en_US
dc.identifier.issn0018-9294
dc.identifier.urihttp://hdl.handle.net/11693/25263
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/10.748984en_US
dc.source.titleIEEE Transactions on Biomedical Engineeringen_US
dc.subjectElectromyogram (EMG)en_US
dc.subjectExercise electrocardiogram (ECG)en_US
dc.subjectOnline orthogonalizationen_US
dc.subjectSignal enhancementen_US
dc.subjectSingular value decomposition (SVD)en_US
dc.subjectAlgorithmsen_US
dc.subjectElectromyographyen_US
dc.subjectSignal filtering and predictionen_US
dc.subjectSignal reconstructionen_US
dc.subjectSignal orthogonalizationen_US
dc.subjectElectrocardiographyen_US
dc.subjectElectrocardiographyen_US
dc.subjectExercise Testen_US
dc.subjectMicrocomputersen_US
dc.titleSVD-based on-line exercise ECG signal orthogonalizationen_US
dc.typeArticleen_US

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