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Proceedings Paper

Phenomenological analysis of medical time series with regular and stochastic components
Author(s): Serge F. Timashev; Yuriy S. Polyakov
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Paper Abstract

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions), which complement the information of each other. The structural function stochastic component is formed exclusively by "jumps" of the dynamic variable while the power spectrum stochastic component is formed by both spikes and "jumps" on every level of the hierarchy. The information "passport" characteristics that are determined by fitting the derived expressions to the experimental variations for the stochastic components of power spectra and structural functions are interpreted as the correlation times and parameters that describe the rate of "memory loss" on these correlation time intervals for different irregularities. The number of the extracted parameters is determined by the requirements of the problem under study. Application of this approach to the analysis of tremor velocity signals for a Parkinsonian patient is discussed.

Paper Details

Date Published: 15 June 2007
PDF: 12 pages
Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 660210 (15 June 2007); doi: 10.1117/12.724571
Show Author Affiliations
Serge F. Timashev, Karpov Institute of Physical Chemistry (Russia)
Yuriy S. Polyakov, USPolyResearch (United States)

Published in SPIE Proceedings Vol. 6602:
Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems
Sergey M. Bezrukov, Editor(s)

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