



@conference {2332,
	title = {Changes in detrended fluctuation indices with aging in healthy and congestive heart failure subjects},
	booktitle = {Computers in CardiologyComput Cardiol},
	series = {Computers in Cardiology 2008, CAR},
	volume = {35},
	year = {2008},
	note = {Conference code: 75561Cited By (since 1996): 1Export Date: 21 November 2012Source: ScopusArt. No.: 4748973CODEN: COCADdoi: 10.1109/CIC.2008.4748973Language of Original Document: EnglishCorrespondence Address: Barquero-P{\'e}rez, {\'O}.; B-013, Universidad Rey Juan Carlos, Camino del Molino s/n, Fuenlabrada-28943 Madrid, Spain; email: obarquero@gmail.comReferences: Goldberger, A.L., Nonlinear dynamics, fractals, and chaos theory: Implications for neuroautonomic heart rate control in health and disease (1999) The Autonomic Nervous System, , Bolis C, Licinnio J eds, Geneva: World Health Organization;Peng, C.K., Havlin, S., Stanley, H.E., Goldberger, A.L., Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series (1995) Chaos, 5, pp. 82-87; 
Goldberger, A.L., Amaral, L.A.N., Hausdorff, J.M., Ivanov, P.C., Peng, C.K., Stanley, H.E., Fractal dynamics in physiology: Alterations with disease and aging (2002) Proceedings of the National Academy of Sciences, 99, p. 119; 
Berger, R.D., Broken fractals: Where{\textquoteright}s the break? (2001) Journal of Cardiovascular Electrophysiology, 12 (1), pp. 33-35; 
Mandelbrot, B.B., van Ness, J.W., Fractional Brownian motions, fractional noises and applications (1968) SIAM Review, 10, pp. 422-437; 
Kantelhardt, J.W., Zschiegner, S.A., Koscielny-Bunde, E., Havlin, S., Bunde, A., Stanley, H.E., Multifractal detrended fluctuations analysis of nonstationary time series (2002) Physica A, 316, pp. 87-114; 
Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Stanley, H.E., PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals (2000) Circulation, 101 (23), pp. e215-e220. , June 13; 
Malik, M., Cripps, T., Farrell, T., Camm, A., Prognostic value of heart rate variability after myocardial infarction. a comparison of different data-processing methods (1989) Medical and Biological Engineering and Computing, 27, pp. 603-621; 
Huikuri, H.V., M{\"a}kikallio, T.H., Perki{\"o}m{\"a}ki, J., Measurement of heart rate variability by methods based on nonlinear dynamics (2003) Journal of Electrocardiology, 36, pp. 95-99; 
Rojo-{\'A}lvarez, J., S{\'a}nchez-S{\'a}nchez, A., Barquero-Prez, O., Goya-Esteban, R., Everss, E., Mora-J{\'\i}menez, I., Garc{\'\i}a-Alberola, A., Analysis of physiological meaning of detrended fluctuation analysis in heart rate variability using a lumped parameter model (2007) Computers in Cardiology, 34, pp. 25-28
},
	month = {2008///},
	pages = {45 - 48},
	address = {Bologna},
	abstract = {Detrended Fluctuation Analysis (DFA) aims to quantify the fractal correlation properties in nonstationary time series, and it has successfully been applied in the assessment of the Heart Rate Variability (HRV) for cardiac risk stratification purposes. However the physiological meaning of DFA indices and its relation with aging have not yet been completely established. Given that a loss of complexity in the physiological regulation of elderly subjects has been reported in the literature, we hypothesized that DFA indices could be modified by aging. In this work we computed the Hurst exponent (estimated using DFA method) and DFA indices α                        1 and α
                        2 to assess the HRV in healthy and Congestive Heart Failure (CHF) subjects, and we studied the dependence of these indices on aging for both healthy and CHF subjects. We found that only α2 and Hurst exponent, and only in the case of healthy subjects, have significant discrimination capability to distinguish between young and elderly groups, and also that these indices have a steady increase with aging. Therefore, we can conclude that the loss of complexity due to aging can be quantified by changes in the values of α
                        2 and Hurst exponent.
},
	keywords = {Cardiology, Congestive heart failures, Correlation properties, Detrended fluctuation analysis, DFA methods, Healthy subjects, Heart rate variabilities, Heart valve prostheses, Hurst exponents, Non-stationary time series, Risk analysis, Risk perception, Risk stratifications, Table lookup, Time series, Time series analysis},
	isbn = {02766574 (ISSN); 1424437067 (ISBN); 9781424437061 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-62249107413\&partnerID=40\&md5=f528b40d49f9968db744c5cd19069493},
	author = {Barquero-P{\'e}rez, {\'O}. and De S{\'a}, J.M. and Rojo-{\'A}lvarez, J.L. and Goya-Esteban, R.}
}
