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Erschienen in: Medical & Biological Engineering & Computing 7/2012

01.07.2012 | Original Article

Modeling the relationship between Higuchi’s fractal dimension and Fourier spectra of physiological signals

verfasst von: Aleksandar Kalauzi, Tijana Bojić, Aleksandra Vuckovic

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 7/2012

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Abstract

The exact mathematical relationship between FFT spectrum and fractal dimension (FD) of an experimentally recorded signal is not known. In this work, we tried to calculate signal FD directly from its Fourier amplitudes. First, dependence of Higuchi’s FD of mathematical sinusoids on their individual frequencies was modeled with a two-parameter exponential function. Next, FD of a finite sum of sinusoids was found to be a weighted average of their FDs, weighting factors being their Fourier amplitudes raised to a fractal degree. Exponent dependence on frequency was modeled with exponential, power and logarithmic functions. A set of 280 EEG signals and Weierstrass functions were analyzed. Cross-validation was done within EEG signals and between them and Weierstrass functions. Exponential dependence of fractal exponents on frequency was found to be the most accurate. In this work, signal FD was for the first time expressed as a fractal weighted average of FD values of its Fourier components, also allowing researchers to perform direct estimation of signal fractal dimension from its FFT spectrum.

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Literatur
1.
Zurück zum Zitat Acharya RU, Faust O, Kannathal N, Chua T, Laxminarayan S (2005) Non-linear analysis of EEG signals at various sleep stages. Comput Method Program Biomed 80:37–45CrossRef Acharya RU, Faust O, Kannathal N, Chua T, Laxminarayan S (2005) Non-linear analysis of EEG signals at various sleep stages. Comput Method Program Biomed 80:37–45CrossRef
2.
Zurück zum Zitat Bhattacharya J (2000) Complexity analysis of spontaneous EEG. Acta Neurobiol Exp 60:495–501 Bhattacharya J (2000) Complexity analysis of spontaneous EEG. Acta Neurobiol Exp 60:495–501
3.
Zurück zum Zitat Bojić T, Vuckovic A, Kalauzi A (2010) Modeling EEG fractal dimension changes in wake and drowsy states in humans—a preliminary study. J Theor Biol 262(2):214–222PubMedCrossRef Bojić T, Vuckovic A, Kalauzi A (2010) Modeling EEG fractal dimension changes in wake and drowsy states in humans—a preliminary study. J Theor Biol 262(2):214–222PubMedCrossRef
4.
Zurück zum Zitat Eke A, Hermann P, Bassingthwaighte JB, Raymond GM, Percival DB, Cannon M, Balla I, Ikrenyi C (2000) Physiological time series: distinguishing fractal noises from motions. Pflug Arch 439:403–415CrossRef Eke A, Hermann P, Bassingthwaighte JB, Raymond GM, Percival DB, Cannon M, Balla I, Ikrenyi C (2000) Physiological time series: distinguishing fractal noises from motions. Pflug Arch 439:403–415CrossRef
5.
Zurück zum Zitat Esteller R, Vachtsevanos G, Echauz J, Litt B (2001) A comparison of waveform fractal dimension algorithms. IEEE Trans Circ Syst I Fundam Theory Appl 48:177–183CrossRef Esteller R, Vachtsevanos G, Echauz J, Litt B (2001) A comparison of waveform fractal dimension algorithms. IEEE Trans Circ Syst I Fundam Theory Appl 48:177–183CrossRef
6.
Zurück zum Zitat Fox CG (1989) Empirically derived relationships between fractal dimension and power law from frequency spectra. Pure Appl Geophys 131(1–2):211–239CrossRef Fox CG (1989) Empirically derived relationships between fractal dimension and power law from frequency spectra. Pure Appl Geophys 131(1–2):211–239CrossRef
7.
Zurück zum Zitat Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Phys D 31:277–283CrossRef Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Phys D 31:277–283CrossRef
8.
Zurück zum Zitat Higuchi T (1990) Relationship between the fractal dimension and the power law index for a time series: a numerical investigation. Physica D 46:254–264CrossRef Higuchi T (1990) Relationship between the fractal dimension and the power law index for a time series: a numerical investigation. Physica D 46:254–264CrossRef
9.
Zurück zum Zitat Kalauzi A, Bojić T, Rakić LJ (2008) Estimation of Higuchi fractal dimension for short signal epochs (<10 samples). In: The 10th experimental chaos conference. Catania, Italy, 3–6 June, pp 89 Kalauzi A, Bojić T, Rakić LJ (2008) Estimation of Higuchi fractal dimension for short signal epochs (<10 samples). In: The 10th experimental chaos conference. Catania, Italy, 3–6 June, pp 89
10.
Zurück zum Zitat Kalauzi A, Bojic T, Rakic Lj (2009) Extracting complexity waveforms from one-dimensional signals. Nonlin Biomed Phys 3:8CrossRef Kalauzi A, Bojic T, Rakic Lj (2009) Extracting complexity waveforms from one-dimensional signals. Nonlin Biomed Phys 3:8CrossRef
11.
Zurück zum Zitat Kalauzi A, Spasić S, Ćulić M, Grbić G, Martać LJ (2004) Correlation between fractal dimension and power spectra after unilateral cerebral injury in rat. In: FENS 2004, Abstracts, vol 2. Lisbon, A199.9 Kalauzi A, Spasić S, Ćulić M, Grbić G, Martać LJ (2004) Correlation between fractal dimension and power spectra after unilateral cerebral injury in rat. In: FENS 2004, Abstracts, vol 2. Lisbon, A199.9
12.
Zurück zum Zitat Kalauzi A, Spasic S, Culic M, Grbic G, Martac Lj (2005) Consecutive differences as a method of signal fractal analysis. Fractals 13(4):283–292CrossRef Kalauzi A, Spasic S, Culic M, Grbic G, Martac Lj (2005) Consecutive differences as a method of signal fractal analysis. Fractals 13(4):283–292CrossRef
13.
14.
Zurück zum Zitat Kunhimangalam R, Joseph PK, Sujith OK (2008) Nonlinear analysis of EEG signals: surrogate data analysis. IRBM 29:239–244CrossRef Kunhimangalam R, Joseph PK, Sujith OK (2008) Nonlinear analysis of EEG signals: surrogate data analysis. IRBM 29:239–244CrossRef
15.
Zurück zum Zitat Lutzenberger W, Elbert T, Birbaumer N, Ray WJ, Schupp H (1992) The scalp distribution of the fractal dimension of the EEG and its validation with mental tasks. Brain Topogr 5(1):27–34PubMedCrossRef Lutzenberger W, Elbert T, Birbaumer N, Ray WJ, Schupp H (1992) The scalp distribution of the fractal dimension of the EEG and its validation with mental tasks. Brain Topogr 5(1):27–34PubMedCrossRef
16.
Zurück zum Zitat Navascués MA, Sebastián MV (2006) Spectral and affine fractal methods in signal processing. Int Math Forum 29:1405–1422 Navascués MA, Sebastián MV (2006) Spectral and affine fractal methods in signal processing. Int Math Forum 29:1405–1422
17.
Zurück zum Zitat Petrosian A (1995) Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns. In: Proceedings of IEEE symposium computer-based med systems, pp 212–217 Petrosian A (1995) Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns. In: Proceedings of IEEE symposium computer-based med systems, pp 212–217
18.
Zurück zum Zitat Sebastián MV, Navascués MA (2008) A relation between fractal dimension and Fourier transform—electroencephalographic study using spectral and fractal parameters. Int J Comp Math 85(3–4):657–665CrossRef Sebastián MV, Navascués MA (2008) A relation between fractal dimension and Fourier transform—electroencephalographic study using spectral and fractal parameters. Int J Comp Math 85(3–4):657–665CrossRef
19.
Zurück zum Zitat Spasić S, Kalauzi A, Ćulić M, Grbić G, Martać Lj (2005) Estimation of parameter kmax in fractal analysis of rat brain activity. Ann NY Acad Sci 1048:427–429PubMedCrossRef Spasić S, Kalauzi A, Ćulić M, Grbić G, Martać Lj (2005) Estimation of parameter kmax in fractal analysis of rat brain activity. Ann NY Acad Sci 1048:427–429PubMedCrossRef
20.
Zurück zum Zitat Spasic S, Kalauzi A, Grbic G, Martac L, Culic M (2005) Fractal analysis of rat brain activity after injury. Med Biol Eng Comput 43:345–348PubMedCrossRef Spasic S, Kalauzi A, Grbic G, Martac L, Culic M (2005) Fractal analysis of rat brain activity after injury. Med Biol Eng Comput 43:345–348PubMedCrossRef
21.
Zurück zum Zitat Spasic S, Kalauzi A, Kesic S, Obradovic M, Saponjic J (2011) Surrogate data modeling the relationship between high frequency amplitudes and Higuchi fractal dimension of EEG signals in anesthetized rats. J Theor Biol 289:160–166PubMedCrossRef Spasic S, Kalauzi A, Kesic S, Obradovic M, Saponjic J (2011) Surrogate data modeling the relationship between high frequency amplitudes and Higuchi fractal dimension of EEG signals in anesthetized rats. J Theor Biol 289:160–166PubMedCrossRef
22.
Zurück zum Zitat Stam CJ (2005) Nonlinear dynamical analysis of EEG and EMG: review of an emerging field. Clin Neurophysiol 116:2266–2301PubMedCrossRef Stam CJ (2005) Nonlinear dynamical analysis of EEG and EMG: review of an emerging field. Clin Neurophysiol 116:2266–2301PubMedCrossRef
23.
Zurück zum Zitat Theil H (1961) Economic forecasts and policy. North Holland, Amsterdam Theil H (1961) Economic forecasts and policy. North Holland, Amsterdam
24.
Zurück zum Zitat Vuckovic A, Radivojevic V, Chen ACN, Popovic D (2002) Automatic recognition of alertness and drowsiness from EEG by an artificial neural network. Med Eng Phys 24:349–360PubMedCrossRef Vuckovic A, Radivojevic V, Chen ACN, Popovic D (2002) Automatic recognition of alertness and drowsiness from EEG by an artificial neural network. Med Eng Phys 24:349–360PubMedCrossRef
25.
Zurück zum Zitat Weiss B, Clemens Z, Bόdisz R, Halász P (2011) Comparison of fractal and power EEG features: effects of topography and sleep stages. Brain Res Bull 84(6):359–375PubMedCrossRef Weiss B, Clemens Z, Bόdisz R, Halász P (2011) Comparison of fractal and power EEG features: effects of topography and sleep stages. Brain Res Bull 84(6):359–375PubMedCrossRef
26.
Zurück zum Zitat Ziller M, Frick K, Herrmann WM, Kubicki S, Spieweg I, Winterer G (1995) Bivariate global frequency analysis versus chaos theory. A comparison for sleep EEG data. Neuropsychobiology 32(1):45–51PubMedCrossRef Ziller M, Frick K, Herrmann WM, Kubicki S, Spieweg I, Winterer G (1995) Bivariate global frequency analysis versus chaos theory. A comparison for sleep EEG data. Neuropsychobiology 32(1):45–51PubMedCrossRef
Metadaten
Titel
Modeling the relationship between Higuchi’s fractal dimension and Fourier spectra of physiological signals
verfasst von
Aleksandar Kalauzi
Tijana Bojić
Aleksandra Vuckovic
Publikationsdatum
01.07.2012
Verlag
Springer-Verlag
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 7/2012
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-012-0913-9

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