Non-linear properties of R-R distributions as a measure of heart rate variability

We analyze the dynamic quality of the R-R interbeat intervals of electrocardiographic signals from healthy people and from patients with premature ventricular contractions (PVCs) by applying different measure algorithms to standardised public domain data sets of heart rate variability. Our aim is to...

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Autor principal: Irurzun, María Isabel
Otros Autores: Bergero, P., Cordero, M.C, Defeo, M.M, Vicente, J.L, Mola, Eduardo Elías
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2003
Acceso en línea:Registro en Scopus
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030 |a CSFOE 
040 |a Scopus  |b spa  |c AR-BaUEN  |d AR-BaUEN 
100 1 |a Irurzun, María Isabel 
245 1 0 |a Non-linear properties of R-R distributions as a measure of heart rate variability 
260 |c 2003 
270 1 0 |m Mola, E.E.; CONICET, Instituto de IFTA, UNLP, Sue. 4, Casilla de Correo 16, La Plata 1900, Argentina; email: eemola@inifta.unlp.edu.ar 
504 |a Dunbar, S.B., Ellenbogen, K., Epstein, A., Sudden cardiac death Past, present and future (1997) Futura 
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504 |a Narayanan, K., Govindan, R.B., Gopinathan, M.S., (1998) Phys. Rev. E, 57 (4), pp. 4594-4603 
504 |a Lathrop, D.P., Kostelich, E.J., (1989) Phys. Rev. A, 40 (7), pp. 4028-4031 
504 |a Dolan, K., Witt, A., Spano, M.L., Neiman, A., Moss, F., (1999) Phys. Rev. E, 59 (5), pp. 5235-5241 
504 |a Glass, L., Hunter, D., (1993) Physica D, 43, p. 1 
504 |a Schreiber, T., (1993) Phys. Rev. E, 48 (1), pp. 13-R16 
504 |a Kostelich, E.J., Schreiber, T., (1993) Phys. Rev. E, 48 (3), pp. 1752-1763 
504 |a Bergero, P., Irurzun, I.M., Vicente, J.L., Mola, E.E., to be published 
506 |2 openaire  |e Política editorial 
520 3 |a We analyze the dynamic quality of the R-R interbeat intervals of electrocardiographic signals from healthy people and from patients with premature ventricular contractions (PVCs) by applying different measure algorithms to standardised public domain data sets of heart rate variability. Our aim is to assess the utility of these algorithms for the above mentioned purposes. Long and short time series, 24 and 0.50 h respectively, of interbeat intervals of healthy and PVC subjects were compared with the aim of developing a fast method to investigate their temporal organization. Two different methods were used: power spectral analysis and the integral correlation method. Power spectral analysis has proven to be a powerful tool for detecting long-range correlations. If it is applied in a short time series, power spectra of healthy and PVC subjects show a similar behavior, which disqualifies power spectral analysis as a fast method to distinguish healthy from PVC subjects. The integral correlation method allows us to study the fractal properties of interbeat intervals of electrocardiographic signals. The cardiac activity of healthy and PVC people stems from dynamics of chaotic nature characterized by correlation dimensions df equal to 3.40±0.50 and 5.00±0.80 for healthy and PVC subjects respectively. The methodology presented in this article bridges the gap between theoretical and experimental studies of non-linear phenomena. From our results we conclude that the minimum number of coupled differential equations to describe cardiac activity must be six and seven for healthy and PVC individuals respectively. From the present analysis we conclude that the correlation integral method is particularly suitable, in comparison with the power spectral analysis, for the early detection of arrhythmias on short time (0.5 h) series. © 2002 Elsevier Science Ltd. All rights reserved.  |l eng 
536 |a Detalles de la financiación: Universidad Nacional de La Plata, UNLP 
536 |a Detalles de la financiación: Universidad Nacional del Centro de la Provincia de Buenos Aires 
536 |a Detalles de la financiación: Consejo Nacional de Investigaciones Científicas y Técnicas 
536 |a Detalles de la financiación: The authors are indebted to the valuable information provided by MIT-BIH Database, Harvard-MIT Division of Health Sciences and Technology. This research project was financially supported by the Consejo Nacional de Investigaciones Cientı́ficas y Técnicas, the Comisión de Investigaciones Cientı́ficas de la Provincia de Buenos Aires and the Universidad Nacional de La Plata. 
593 |a CONICET, Instituto de IFTA, UNLP, Sue. 4, Casilla de Correo 16, La Plata 1900, Argentina 
593 |a Fac. de Ciencias Exactas y Naturales, Departamento de Física, Universidad de Buenos Aires, Buenos Aires 1428, Argentina 
593 |a Servicio de Cardiología, Hospital Prof. Rodolfo Rossi, La Plata 1900, Argentina 
690 1 0 |a ALGORITHMS 
690 1 0 |a CARDIOLOGY 
690 1 0 |a CHAOS THEORY 
690 1 0 |a CORRELATION METHODS 
690 1 0 |a DIFFERENTIAL EQUATIONS 
690 1 0 |a ELECTROCARDIOGRAPHY 
690 1 0 |a FRACTALS 
690 1 0 |a INTEGRAL EQUATIONS 
690 1 0 |a SPECTRUM ANALYSIS 
690 1 0 |a HEART RATE VARIABILITY 
690 1 0 |a NONLINEAR SYSTEMS 
700 1 |a Bergero, P. 
700 1 |a Cordero, M.C. 
700 1 |a Defeo, M.M. 
700 1 |a Vicente, J.L. 
700 1 |a Mola, Eduardo Elías 
773 0 |d 2003  |g v. 16  |h pp. 699-708  |k n. 5  |p Chaos Solitons Fractals  |x 09600779  |w (AR-BaUEN)CENRE-4143  |t Chaos, Solitons and Fractals 
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856 4 0 |u https://doi.org/10.1016/S0960-0779(02)00403-4  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_09600779_v16_n5_p699_Irurzun  |y Handle 
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