Time-Varying Cardiovascular Oscillations
作者： V. N. Smelyanskiy , D. A. Timucin , D. G. Luchinsky , A. Stefanovska , A. Bandrivskyy
DOI: 10.1007/978-94-010-0179-3_40
关键词: Identification (information) 、 Inference 、 Hilbert–Huang transform 、 Nonlinear system 、 Van der Pol oscillator 、 Algorithm 、 Rapid convergence 、 Bayesian inference 、 Computer science 、 Probability density function
摘要: Signals derived from the human cardiovascular system (CVS) are exceptionally complex, being time-varying, noisy, and of necessarily limited duration. Yet an appropriate analysis them may be expected to yield detailed information about dynamics underlying physiological processes. A new approach modelhng CVS signals is proposed. It combines decomposition into principal modes a novel method parameter identification in nonlinear stochastic systems based on Bayesian inference. The scheme tested noisy Van der Pol oscillator, for which it yields rapid convergence correct inference known parameters. Preliminary applications data discussed.
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