A comparison of two Hilbert spectral analyses of heart rate variability

Original Article

Abstract

The present paper compares the performance of two Hilbert spectral analyses when applied to a synthetic RR series from a nonstationary integral pulse frequency modulation model and to real RR series from a dataset of normal sinus arrhythmia. The Hilbert–Huang transformation based on empirical mode decomposition is compared to the presently introduced Hilbert–Olhede–Walden transformation based on stationary wavelet packet decomposition. The comparison gives consistent results pointing to a superior performance of the Hilbert–Olhede–Walden transformation showing 33–163 times smaller deviations when estimating the instantaneous frequency traces of the synthetic RR series. Artificial fluctuations caused by mode mixing in the Hilbert–Huang spectrum are seen in both the synthetic and real RR series. It can be concluded that the instantaneous frequencies and amplitudes estimated by the Hilbert–Huang transformation should be interpreted with caution when investigating heart rate variability.

Keywords

Heart rate variability Hilbert–Huang spectrum Empirical mode decomposition Integral pulse frequency modulation Instantaneous frequency Wavelet transformation Time–frequency analysis 

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Copyright information

© International Federation for Medical and Biological Engineering 2009

Authors and Affiliations

  1. 1.Human Movement Science ProgrammeNorwegian University of Science and TechnologyTrondheimNorway

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