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dc.contributor.authorGarde Martínez, Ainara
dc.contributor.authorSörnmo, Leif
dc.contributor.authorJané Campos, Raimon
dc.contributor.authorGiraldo Giraldo, Beatriz
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherInstitut de Bioenginyeria de Catalunya
dc.date.accessioned2010-10-25T11:01:03Z
dc.date.available2010-10-25T11:01:03Z
dc.date.created2010-08
dc.date.issued2010-08
dc.identifier.citationGarde, A. [et al.]. Correntropy-based spectral characterization of respiratory Patterns in patients with chronic heart failure. "IEEE transactions on biomedical engineering", Agost 2010, vol. 57, núm. 8, p. 1964-1972.
dc.identifier.issn0018-9294
dc.identifier.urihttp://hdl.handle.net/2117/9961
dc.description.abstractA correntropy-based technique is proposed for the characterization and classification of respiratory flow signals in chronic heart failure (CHF) patients with periodic or nonperiodic breathing (PB or nPB, respectively) and healthy subjects. The correntropy is a recently introduced, generalized correlation measure whose properties lend themselves to the definition of a correntropybased spectral density (CSD). Using this technique, both respiratory and modulation frequencies can be reliably detected at their original positions in the spectrum without prior demodulation of the flow signal. Single-parameter classification of respiratory patterns is investigated for three different parameters extracted from the respiratory and modulation frequency bands of the CSD, and one parameter defined by the correntropy mean. The results show that the ratio between the powers in the modulation and respiratory frequency bands provides the best result when classifying CHF patients with either PBor nPB, yielding an accuracy of 88.9%. The correntropy mean offers excellent performance when classifying CHF patients versus healthy subjects, yielding an accuracy of 95.2% and discriminating nPB patients fromhealthy subjects with an accuracy of 94.4%.
dc.format.extent9 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
dc.subject.lcshAutoregressive processes (cardiology)
dc.subject.lcshMedical signal processing
dc.subject.lcshPeumodynamics
dc.subject.lcshChronic heart failure (CHF)
dc.titleCorrentropy-based spectral characterization of respiratory Patterns in patients with chronic heart failure
dc.typeArticle
dc.subject.lemacCor -- Malalties -- Diagnòstic
dc.contributor.groupUniversitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics
dc.identifier.doi10.1109/TBME.2010.2044176
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
drac.iddocument3095438
dc.description.versionPostprint (published version)
upcommons.citation.authorGarde, A.; Sörnmo, L.; Jané, R.; Giraldo, B. F.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameIEEE transactions on biomedical engineering
upcommons.citation.volume57
upcommons.citation.number8
upcommons.citation.startingPage1964
upcommons.citation.endingPage1972


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