Ordinal patterns with ties and tolerance provide a physiology-driven method to quantify cardiorespiratory interactions

Abstract

We propose a new analytical approach based on ordinal pattern analysis to investigate respiratory heart rate variability (RespHRV, also called respiratory sinus arrhythmia), specifically modulation of heart rate across different phases of the respiratory cycle. The method uses RR interval time series derived from ECG signals, along with simultaneous respiratory recordings obtained with a respiratory belt. The method produces distributions of ordinal patterns that reflect the dynamics of heart rate variability throughout the respiratory cycle. We systematically test how variations in parameters defining ordinal patterns affect the results and interpretation, and discuss the optimal parameter configuration for quantification of RespHRV in short-term recordings. Finally, we demonstrate the ability of the method to differentiate between healthy controls and patients with obstructive sleep apnea based on daytime cardiorespiratory data.