000061851 001__ 61851
000061851 005__ 20200221144311.0
000061851 0247_ $$2doi$$a10.1007/s11517-016-1498-5
000061851 0248_ $$2sideral$$a94967
000061851 037__ $$aART-2016-94967
000061851 041__ $$aeng
000061851 100__ $$aGarde, Ainara
000061851 245__ $$aAssessment of respiratory flow cycle morphology in patients with chronic heart failure
000061851 260__ $$c2016
000061851 5060_ $$aAccess copy available to the general public$$fUnrestricted
000061851 5203_ $$aBreathing pattern as periodic breathing (PB) in chronic heart failure (CHF) is associated with poor prognosis and high mortality risk. This work investigates the significance of a number of time domain parameters for characterizing respiratory flow cycle morphology in patients with CHF. Thus, our primary goal is to detect PB pattern and identify patients at higher risk. In addition, differences in respiratory flow cycle morphology between CHF patients (with and without PB) and healthy subjects are studied. Differences between these parameters are assessed by investigating the following three classification issues: CHF patients with PB versus with non-periodic breathing (nPB), CHF patients (both PB and nPB) versus healthy subjects, and nPB patients versus healthy subjects. Twenty-six CHF patients (8/18 with PB/nPB) and 35 healthy subjects are studied. The results show that the maximal expiratory flow interval is shorter and with lower dispersion in CHF patients than in healthy subjects. The flow slopes are much steeper in CHF patients, especially for PB. Both inspiration and expiration durations are reduced in CHF patients, mostly for PB. Using the classification and regression tree technique, the most discriminant parameters are selected. For signals shorter than 1 min, the time domain parameters produce better results than the spectral parameters, with accuracies for each classification of 82/78, 89/85, and 91/89 %, respectively. It is concluded that morphologic analysis in the time domain is useful, especially when short signals are analyzed.
000061851 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000061851 590__ $$a1.916$$b2016
000061851 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b52 / 105 = 0.495$$c2016$$dQ2$$eT2
000061851 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b15 / 57 = 0.263$$c2016$$dQ2$$eT1
000061851 591__ $$aMEDICAL INFORMATICS$$b12 / 23 = 0.522$$c2016$$dQ3$$eT2
000061851 591__ $$aENGINEERING, BIOMEDICAL$$b40 / 77 = 0.519$$c2016$$dQ3$$eT2
000061851 592__ $$a0.712$$b2016
000061851 593__ $$aComputer Science Applications$$c2016$$dQ2
000061851 593__ $$aBiomedical Engineering$$c2016$$dQ2
000061851 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000061851 700__ $$aSörnmo, Leif
000061851 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza
000061851 700__ $$aJané, Raimon
000061851 700__ $$aBenito, Salvador
000061851 700__ $$aBayés-Genís, Antoni
000061851 700__ $$aGiraldo, Beatriz F.
000061851 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000061851 773__ $$g55, 2 (2016), 245-255$$pMed. biol. eng. comput.$$tMEDICAL & BIOLOGICAL ENGINEERING & COMPUTING$$x0140-0118
000061851 8564_ $$s261137$$uhttps://zaguan.unizar.es/record/61851/files/texto_completo.pdf$$yPostprint
000061851 8564_ $$s49521$$uhttps://zaguan.unizar.es/record/61851/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000061851 909CO $$ooai:zaguan.unizar.es:61851$$particulos$$pdriver
000061851 951__ $$a2020-02-21-13:37:06
000061851 980__ $$aARTICLE