title: Multiple window correlation analysis of HRV power and respiratory frequency.
abstract: In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, between the respiratory center frequency and the high-frequency band of the heartrate variability (HRV) power. One aim is to examine whether a more restricted frequency range would better capture respiratory related HR variation, especially when the HR variation is changing rapidly. The respiratory peak is detected and a narrow-banded measure of the high-frequency (HF) band of the HRV is defined as the respiratory frequency +/-0.05 Hz. We compare the mean square error of the correlation estimate between the frequency of the respiratory peak and the power of the HRV with the power in the usual 0.12-0.4 Hz frequency band. Different multiple window spectrum techniques are used for the estimation of the respiratory frequency as well as for the power of the HRV. We compare the peak-matched multiple windows with the Welch method while evaluating the two different HF-power estimates mentioned above. The results show that using a more narrow band for the power estimation gives stronger correlation which indicates that the estimate of the power is more robust.
authors.affiliation: Centre for Mathematical Sciences, Mathematical Statistics, Lund University, Box 118, SE-221 00 Lund, Sweden.
authors.forename: Maria
authors.initials: M
authors.lastname: Hansson-Sandsten
authors.forename: Peter
authors.initials: P
authors.lastname: Jönsson
mesh_terms: D000465:Algorithms; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D015656:Respiratory Mechanics / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic