title: A comparison of two Hilbert spectral analyses of heart rate variability.
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.
authors.affiliation: Norwegian University of Science and Technology, Dragvoll Idrettssenter, 7491, Trondheim, Norway. espenale@svt.ntnu.no
authors.forename: Espen Alexander Fürst
authors.initials: EA
authors.lastname: Ihlen
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D004562:Electrocardiography / Q000379:methods; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted