"JOURNAL OF RADIO ELECTRONICS" (Zhurnal Radioelektroniki ISSN 1684-1719, N 9, 2016

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The problem of solving the Hilbert-Huang transform application for biomedical signal processing based on CEEMDAN method


V. D. Ompokov, V. V. Boronoyev

Institute of Physical Materials Science of SB RAS

The paper is received on September 21, 2016

Abstract. The most promising method of time-frequency analysis of the data is the Hilbert-Huang Transform, which makes it possible to work with nonstationary and nonlinear data. The method is based on the Empirical Mode Decomposition of signals and the Hilbert Transform. The key feature of Empirical Mode Decomposition is to decompose a signal into so-called Intrinsic Mode Function (IMF). IMF represents a simple oscillatory mode as a counterpart to the simple harmonic function, but it is much more general: instead of constant amplitude and frequency in a simple harmonic component, an IMF can have variable amplitude and frequency along the time axis. Further-more, the Hilbert Spectral Analysis of Intrinsic Mode Functions provides frequency information evolving with time and quantifies the amount of variation due to oscillation at different time scales and time locations. The paper shows problems solving of applying Hilbert-Huang Transform for biomedical signal processing. It is the presence of oscillations of very disparate amplitude in a mode, or the presence of very similar oscillations in different modes. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) can effectively overcome these problems, and potentially should provide more objective results than alternative methods. In the CEEMDAN method a particular noise is added at each stage of the decomposition and a unique residue is computed to obtain each mode.

Key words: pulse signal, Hilbert-Huang transform, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise.


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