In this chapter the authors deal with a few methods of nonlinear wavelet analysis for the characterization of nonstationary signals. The methods herein described can be used in a wide variety of biological signals including ECG, HRV, pressure waves and heart sounds. The reader can find both conventional methods of wavelet analysis such as linear and nonlinear denoising, as well as more sophisticated methods based on fractal analysis and entropy. Applications of such algorithms to the analysis of the heartbeat dynamics are also described.
Introduction to complex systems analysis with wavelets
Vanello, Nicola
Writing – Original Draft Preparation
;Landini, LuigiWriting – Original Draft Preparation
2017-01-01
Abstract
In this chapter the authors deal with a few methods of nonlinear wavelet analysis for the characterization of nonstationary signals. The methods herein described can be used in a wide variety of biological signals including ECG, HRV, pressure waves and heart sounds. The reader can find both conventional methods of wavelet analysis such as linear and nonlinear denoising, as well as more sophisticated methods based on fractal analysis and entropy. Applications of such algorithms to the analysis of the heartbeat dynamics are also described.File in questo prodotto:
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