# Physiological Noise in Cardiorespiratory Time-Varying Interactions

## TL;DR

This paper introduces a method to detect physiological noise in cardiorespiratory interactions using Bayesian inference, revealing how different breathing patterns affect noise levels.

## Contribution

The novel contribution is a methodological framework using dynamical Bayesian inference to detect dynamic physiological noise in oscillatory systems.

## Key findings

- Different breathing patterns significantly affect the physiological noise in respiration dynamics.
- Perturbations in breathing do not translate into changes in the dynamic noise of cardiac dynamics.
- The framework shows potential for broader applications in other physiological systems.

## Abstract

The systems in nature are rarely isolated and there are different influences that can perturb their states. Dynamic noise in physiological systems can cause fluctuations and changes on different levels, often leading to qualitative transitions. In this study, we explore how to detect and extract the physiological noise, in terms of dynamic noise, from measurements of biological oscillatory systems. Moreover, because the biological systems can often have deterministic time-varying dynamics, we have considered how to detect the dynamic physiological noise while at the same time following the time-variability of the deterministic part. To achieve this, we use dynamical Bayesian inference for modeling stochastic differential equations that describe the phase dynamics of interacting oscillators. We apply this methodological framework on cardio-respiratory signals in which the breathing of the subjects varies in a predefined manner, including free spontaneous, sine, ramped and aperiodic breathing patterns. The statistical results showed significant difference in the physiological noise for the respiration dynamics in relation to different breathing patterns. The effect from the perturbed breathing was not translated through the interactions on the dynamic noise of the cardiac dynamics. The fruitful cardio-respiratory application demonstrated the potential of the methodological framework for applications to other physiological systems more generally.