Key result
Systematic classification divides biomedical time series variability analysis methods into linear and nonlinear techniques.
Why the study?
The study was conducted to systematize methods for time series variability analysis used in physiological and biomedical research.
Design
Review
May aid clinical time series variability analysis in cardiology; leaves open optimal techniques for predicting patient outcomes.
This article aims to systematize the methods for the time series (TS) variability analysis, as employed in physiological and biomedical research. We propose a classification of these methods, describe linear and nonlinear TS analysis techniques, and provide examples of their biomedical application. The presented information is supposed to be helpful for future researchers in gaining a comprehensive knowledge of the latest trends in biomedical TS analysis and prospects for their application.
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Grishin et al. (2026) studied this question. Biomedical time series variability analysis methods are systematically classified into linear and nonlinear techniques to guide future physiological research applications.
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