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.

Biomedical Center Martin Jessenius Faculty of Medicine in Martin Comenius University in Bratislava Mala Hora 4C 036 01 Martin Slovak Republic

Department of Medical Biophysics Jessenius Faculty of Medicine in Martin Comenius University in Bratislava Mala Hora 4 036 01 Martin Slovak Republic

Department of Physiology Jessenius Faculty of Medicine in Martin Comenius University in Bratislava Mala Hora 4C 036 01 Martin Slovak Republic

Institute of Scientific Instruments The Czech Academy of Sciences Kralovopolska 147 612 00 Brno Czech Republic

International Clinical Research Center St Anne's University Hospital Pekarska 53 656 91 Brno Czech Republic

Pediatric Cardiology Kollarova 13 036 01 Martin Slovak Republic

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