Literature DB >> 1885430

Applications of fractal analysis to physiology.

R W Glenny1, H T Robertson, S Yamashiro, J B Bassingthwaighte.   

Abstract

This review describes approaches to the analysis of fractal properties of physiological observations. Fractals are useful to describe the natural irregularity of physiological systems because their irregularity is not truly random and can be demonstrated to have spatial or temporal correlation. The concepts of fractal analysis are introduced from intuitive, visual, and mathematical perspectives. The regional heterogeneities of pulmonary and myocardial flows are discussed as applications of spatial fractal analysis, and methods for estimating a fractal dimension from physiological data are presented. Although the methods used for fractal analyses of physiological data are still under development and will require additional validation, they appear to have great potential for the study of physiology at scales of resolution ranging from the microcirculation to the intact organism.

Mesh：

Year:  1991        PMID： 1885430      PMCID： PMC4063444          DOI： 10.1152/jappl.1991.70.6.2351

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN： 0161-7567


  26 in total

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Authors:  E R WEIBEL; D M GOMEZ
Journal:  Science       Date:  1962-08-24       Impact factor: 47.728

2.  Modeling of lung morphogenesis using fractal geometries.

Authors:  T R Nelson; D K Manchester
Journal:  IEEE Trans Med Imaging       Date:  1988       Impact factor: 10.048

3.  How long is the coast of britain? Statistical self-similarity and fractional dimension.

Authors:  B Mandelbrot
Journal:  Science       Date:  1967-05-05       Impact factor: 47.728

4.  Diameters, generations, and orders of branches in the bronchial tree.

Authors:  K Horsfield
Journal:  J Appl Physiol (1985)       Date:  1990-02

5.  Fractal nature of regional myocardial blood flow heterogeneity.

Authors:  J B Bassingthwaighte; R B King; S A Roger
Journal:  Circ Res       Date:  1989-09       Impact factor: 17.367

6.  A new model for biological pattern formation.

Authors:  P Meakin
Journal:  J Theor Biol       Date:  1986-01-07       Impact factor: 2.691

7.  On a mechanism of cardiac electrical stability. The fractal hypothesis.

Authors:  A L Goldberger; V Bhargava; B J West; A J Mandell
Journal:  Biophys J       Date:  1985-09       Impact factor: 4.033

8.  Teleonomical optimization of a fractal model of the pulmonary arterial bed.

Authors:  J Lefèvre
Journal:  J Theor Biol       Date:  1983-05-21       Impact factor: 2.691

9.  Fractal surfaces of proteins.

Authors:  M Lewis; D C Rees
Journal:  Science       Date:  1985-12-06       Impact factor: 47.728

10.  Morphometry of the small pulmonary arteries in man.

Authors:  K Horsfield
Journal:  Circ Res       Date:  1978-05       Impact factor: 17.367
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  34 in total

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4.  Effects and significance of premature beats on fractal correlation properties of R-R interval dynamics.

Authors:  Mirja A Peltola; Tapio Seppänen; Timo H Mäkikallio; Heikki V Huikuri
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6.  Low morphometric complexity of emphysematous lesions predicts survival in chronic obstructive pulmonary disease patients.

Authors:  Jeongeun Hwang; Yeon-Mok Oh; Minho Lee; Seunghyun Choi; Joon Beom Seo; Sang Min Lee; Namkug Kim
Journal:  Eur Radiol       Date:  2018-06-29       Impact factor: 5.315

7.  A comparative analysis of spectral exponent estimation techniques for 1/f(β) processes with applications to the analysis of stride interval time series.

Authors:  Alexander Schaefer; Jennifer S Brach; Subashan Perera; Ervin Sejdić
Journal:  J Neurosci Methods       Date:  2013-11-04       Impact factor: 2.390

8.  Power-law kinetics of tracer washout from physiological systems.

Authors:  D A Beard; J B Bassingthwaighte
Journal:  Ann Biomed Eng       Date:  1998 Sep-Oct       Impact factor: 3.934

Review 9.  A healthy dose of chaos: Using fractal frameworks for engineering higher-fidelity biomedical systems.

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10.  Most suitable mother wavelet for the analysis of fractal properties of stride interval time series via the average wavelet coefficient method.

Authors:  Zhenwei Zhang; Jessie VanSwearingen; Jennifer S Brach; Subashan Perera; Ervin Sejdić
Journal:  Comput Biol Med       Date:  2016-11-26       Impact factor: 4.589
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