Respiratory sinus arrhythmia (RSA) is an index of cardiovagal regulation, emotional and cognitive processing. RSA is quantified using heart rate variability (HRV) spectral analysis at respiratory-linked high-frequency band (HF-HRV) using Fast Fourier transformation (FFT) or autoregressive (AR) method, both requiring resampling of recordings - a potential source of error. We hypothesized that rarely used HRV time-frequency analysis with Lomb-Scargle periodogram (LSP) without resampling could be more sensitive to detect neurocardiac response to posture change than FFT and AR. Orthostasis (posture change from supine to standing) evoked significant decrease of HF-HRV well detectable by FFT, AR, and LSP. In contrast, during posture change from sitting to lying, significant increase of HF-HRV and peak HF was best detected using LSP. In regression analysis, the associations between RR-interval, HF-HRV, and peak HF were best detected when evaluated using LSP. Time-frequency HRV analysis with LSP could represent an important alternative to conventional FFT and AR methods for assessment of cardiovagal regulation indexed by RSA.

• MeSH
• časové faktory MeSH
• dechová frekvence fyziologie   MeSH
• elektrokardiografie MeSH
• Fourierova analýza MeSH
• lidé MeSH
• mladiství MeSH
• neparametrická statistika MeSH
• regresní analýza MeSH
• respirační sinusová arytmie fyziologie   MeSH
• srdeční frekvence fyziologie   MeSH
• Check Tag
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH