A broken power-law model of heart rate variability spectra in sleep
Schneider, B.; Dresler, M.; Gombos, F.; Kovacs, I.; Bodizs, R.
Show abstract
AimsThe aim of the study was to introduce a parametric description of RR-interval spectra using a broken power-law model, in addition to the parametrization of oscillatory peaks. Furthermore, to use this model to evaluate effects of age, sex and sleep architecture on overnight heart rate variability (HRV) in healthy subjects. Methods & ResultsFrom a polysomnography database, 215 whole-night, high quality electrocardiograms (ECGs) were extracted. The fractal and oscillatory power-spectral densities (PSDs) were calculated from evenly resampled RR-interval time-series, then a broken power-law model was fitted using piecewise linear regression to the double-logarithmic PSD, determining a custom breaking point in the fractal component, and allowing for two independent spectral slopes in the lower and higher frequency domains. The two-slope model provided a more optimal description compared to linear regression in all cases, even when penalizing increased model complexity. Peak detection was applied to the oscillatory component in the LF (0.04-0.15 Hz) and HF (0.15-0.4 Hz) bands, extracting the frequency and prominence of the dominant peak from each. The high frequency domain intercept, the breaking point frequency and the LF peak frequency decreased significantly with age. Both slopes were flatter in females, while the high domain intercept and the HF peak prominence was significantly increased. Waking after sleep onset and lightest sleep (N1) were associated with lower intercept values, while REM sleep had an opposite effect. ConclusionsThe broken power-law model proved to be more appropriate for the description of RR-interval spectra than the single-slope model, and also captured effects of age, sex and sleep structure that were corroborated by the literature. We would like to highlight that while HRV changes are often assumed to be of oscillatory origin, the fractal component has a major contribution to the total PSD, and thus to all measures derived from it.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Subjective sleep onset latency is influenced by sleep structure and body heat loss in human subjects 94%
- Looking for a reference for large datasets: relative reliability of visual and automatic sleep scoring 94%
- Automated real-time EEG sleep spindle detection for brain state-dependent brain stimulation 93%
Similar papers in this journal
- Comparisons of Heart Rate Variability Responses to Head-up Tilt With and Without Abdominal and Lower-Extremity Compression in Healthy Young Individuals: A Randomized Crossover Study 91%
- Effective Assessments of a Short-duration Poor Posture on Upper Limb Muscle Fatigue before Physical Exercise 91%
- Occurrence of relative bradycardia and relative tachycardia in individuals diagnosed with COVID-19 91%
Similar papers in this journal
- Is sleep apnea-hypopnea index relevant for impaired brain perfusion and desaturation in patients with severe obstructive sleep apnea syndromes? 95%
- Short-Term Meditation Training Alters Brain Activity and Sympathetic Responses at Rest, but not during the meditation 93%
- The relationship between subjective sleep quality and cognitive performance in healthy young adults: Evidence from three empirical studies 93%
Similar papers in this journal
- Comparison of feature-based indices derived from photoplethysmogram recorded from different body locations during lower body negative pressure 92%
- An Open-Access Simultaneous Electrocardiogram and Phonocardiogram Database 92%
- Cycle-frequency content EEG analysis improves the assessment of respiratory-related cortical activity 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.