Key result
Nonlinear time series analysis demonstrated that human photoplethysmogram dynamics are consistent with chaotic movement, showing similarity to Rossler's single band chaos.
Observational
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Photoplethysmogram signals exhibit deterministic chaotic dynamics, which can be analyzed using nonlinear time series tools for theoretical and applied cardiovascular studies.
The photoplethysmogram is widely used in medical settings and sports equipment to measure biological signals. The photoplethysmogram, which is measured noninvasively, can provide valuable information about cardiovascular system performance. The present study sought to investigate the underlying dynamics of photoplethysmographic signals from healthy young human subjects. In previous studies the photoplethysmogram was claimed to be driven by deterministic chaos [Tsuda 1992, Sumida 2000]; however, the methods applied for chaos detection were noise sensitive and inconclusive. Therefore, to reach a consistent conclusion it is important to employ additional nonlinear time series analysis tools that can test different features of the signal's underlying dynamics. In this paper, methods of nonlinear time series analysis, including time delay embedding, largest Lyapunov exponent, deterministic nonlinear prediction, Poincaré section, the Wayland test and method of surrogate data were applied to photoplethysmogram time series to identify the unique characteristics of the photoplethysmogram as a dynamical system. Results demonstrated that photoplethysmogram dynamics is consistent with the definition of chaotic movement, and its chaotic properties showed some similarity to Rossler's single band chaos with induced dynamical noise. Additionally it was found that deterministic nonlinear prediction, Poincaré section and the Wayland test can reveal important characteristics of photoplethysmographic signals that will be important tools for theoretical and applied studies on the photoplethysmogram.
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Sviridova et al. (2015) conducted an observational in Healthy. Nonlinear time series analysis was evaluated on Underlying dynamics and chaotic characteristics of photoplethysmographic signals. Nonlinear time series analysis demonstrated that human photoplethysmogram dynamics are consistent with chaotic movement, showing similarity to Rossler's single band chaos.
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