Key result
Autoregressive and FFT spectral analyses of heart rate variability showed significant differences in the supine position, but both methods provided consistent dynamic trends during passive tilt.
Why the study?
Does autoregressive spectral analysis differ from fast Fourier transform in assessing heart rate variability during passive tilt in healthy subjects?
Observational (n=18)
Does autoregressive spectral analysis differ from fast Fourier transform in assessing heart rate variability during passive tilt in healthy subjects?
While AR and FFT spectral analyses yield significantly different absolute values for heart rate variability components, their dynamic trends during tilt testing remain consistent.
AR-FFT differences in supine HRV but comparable tilt trends leave optimal PSD method unresolved; standardization needed before wider use.
The dynamic response of the autonomic nervous system during tilting is assessed by changes in the low (LF) and high frequency (HF) components of the RR series power spectral density (PSD). Although results of many studies are consistent, some doubts related to different methodologies remain. Specifically, the respective relevance of autoregressive (AR) and fast Fourier transform (FFT) methods is often questioned. Beat-to-beat RR series were recorded during 90 degrees passive tilt in 18 healthy subjects (29 +/- 5 years, eight females). FFT-based (50% overlap, Hanning window) and AR-based (Levinson-Durbin algorithm) PSDs were calculated on the same RR intervals. Powers in very low frequency (VLF: < 0.04 Hz), LF (0.04-0.15 Hz), and HF (0.15-0.40 Hz) bands were calculated either by spectrum integration (FFT and ARIN), by considering the highest AR component in each band (ARHP), or by summation of all AR components (ARAP). LF and HF raw powers (ms2) were normalized by total power (%P) and by total power after removal of the VLF component (nu). AR and FFT total powers were not different, regardless of body position. In supine condition, when compared to ARHP and ARAP, FFT underestimated VLF and overestimated LF, whereas in tilt position FFT overestimated HF and underestimated LF. However, supine/tilt trends were consistent in all methods showing a clear reduction of HF and a less marked increase of LF. Both normalization procedures provided a significant LF increase and further magnified the HF decrease. Results obtained with ARIN were remarkably close to those obtained with FFT. In conclusion, significant differences between AR and FFT spectral analyses do exist, particularly in supine position. Nevertheless, dynamic trends provided by the two approaches are consistent. Normalization is necessary to evidence the LF increase during tilt.
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Badilini et al. (1998) conducted an observational in Healthy (n=18). Autoregressive (AR) spectral analysis vs. Fast Fourier transform (FFT) spectral analysis was evaluated on Power spectral density (VLF, LF, HF bands) of RR series. Autoregressive and FFT spectral analyses of heart rate variability showed significant differences in the supine position, but both methods provided consistent dynamic trends during passive tilt.
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