The impact of controlled breathing on autonomic nervous system modulation: analysis using phase-rectified signal averaging, entropy and heart rate variability.

Abstract

Objective The present study investigated how breathing stimuli affect both non-linear and linear metrics of the autonomic nervous system (ANS). Approach The analyzed dataset consisted of 70 young, healthy volunteers, in whom arterial blood pressure (ABP) was measured noninvasively during 5-minute sessions of controlled breathing at three different frequencies: 6, 10, and 15 breaths/min. CO2 concentration and respiratory rate were continuously monitored throughout the controlled breathing sessions. The ANS was characterized using non-linear methods, including Phase-Rectified Signal Averaging (PRSA) for estimating heart acceleration and deceleration capacity (AC, DC), multiscale entropy (MSEn), approximate entropy (ApEn), sample entropy (SampEn), and fuzzy entropy (FuzzyEn), as well as time and frequency domains (low frequency, LF; high-frequency, HF; total power, TP) of heart rate variability (HRV). Main Results Higher breathing rates resulted in a significant decrease in end-tidal CO2 concentration (p < 0.001), accompanied by increases in both ABP (p<0.001) and heart rate (p<0.001). A strong, linear decline in AC and DC (p<0.001 for both) was observed with increasing respiratory rate. All entropy metrics increased with breathing frequency (p<0.001). In the time-domain, HRV metrics significantly decreased with breathing frequency (p<0.01 for all). In the frequency-domain, HRV LF and HRV HF decreased (p = 0.038 and p = 0.040, respectively), although these changes were modest. There was no significant change in HRV TP with breathing frequencies. Significance Alterations in CO2 levels, a potent chemoreceptor trigger, and changes in HR most likely modulate ANS metrics. Non-linear PRSA and entropy appear to be more sensitive to breathing stimuli compared to frequency-dependent HRV metrics. Further research involving a larger cohort of healthy subjects is needed to validate our observations. .