Statistical physics and physiology: Monofractal and multifractal approaches

Even under healthy, basal conditions, physiologic systems show erratic fluc tuations resembling those found in dynamical systems driven away from a sin gle equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by extern al and intrinsic noise? Or, do these fluctuations actually contain useful, "hidden" information about the underlying nonequilibrium control mechanisms ? We report some recent attempts to understand the dynamics of complex phys iologic fluctuations by adapting and extending concepts and methods develop ed very recently in statistical physics, Specifically, we focus on interbea t interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is read ily measured by noninvasive means, and (iii) analysis of these heart I ate dynamics may provide important practical diagnostic and prognostic informat ion not obtainable with current approaches, The analytic tools we discuss m ay be used on a wider range of physiologic signals. We first review recent progress using two analysis methods - detrended fluctuation analysis and wa velets - sufficient for quantifying monofractal structures. We then describ e very recent work that quantifies multifractal features of interbeat inter val series, and the discovery that the multifractal structure of healthy su bjects is different than that of diseased subjects, (C) 1999 Published by E lsevier Science B,V, All rights reserved.