ESGCO 2022 Challenge: Joint Symbolic Analysis Characterizes Cardiorespiratory Coupling in Healthy Subjects

Abstract

Some aspects of cardiorespiratory coupling (CRC) require tools capable of accounting for nonlinearities. Joint symbolic analysis (JSA) has been proposed to characterize CRC via the rate of short, jointly coordinated (C), patterns obtained from the heart period (HP) variability and respiration (R) series. C schemes were distinguished according to the dominant time scale governing CRC. We applied JSA to a database of 19 healthy subjects (age: 27–35 yrs, median = 31 yrs; 8 males) during spontaneous and paced breathing at varying respiratory rates. The rate of C pattern did not vary with the breathing rate, but the proportions of C pattern families changed with respiratory frequency. We conclude that JSA is a useful tool to investigate the effect of breathing patterns on CRC, with potential applications in patients with respiratory failure such as that developed in COVID-19 syndrome.