Quantification of Cardiorespiratory Interactions Based on Joint Symbolic Dynamics

• Published in: Annals of biomedical engineering 2011-10, Vol.39 (10), p.2604-2614
• Main Authors: Kabir, Muammar M., Saint, David A., Nalivaiko, Eugene, Abbott, Derek, Voss, Andreas, Baumert, Mathias
• Format: Article
• Language: English
• Subjects: Algorithms; Arrhythmia, Sinus - physiopathology; Autonomic Nervous System - physiology; Biochemistry; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Classical Mechanics; Electrocardiography; Female; Heart Rate - physiology; Humans; Male; Pattern Recognition, Automated - methods; Posture - physiology; Respiratory Mechanics - physiology; Respiratory Rate - physiology; Time series; Young Adult
• ISSN: 0090-6964; 1573-9686
• DOI: 10.1007/s10439-011-0332-3

Cardiac and respiratory rhythms are highly nonlinear and nonstationary. As a result traditional time-domain techniques are often inadequate to characterize their complex dynamics. In this article, we introduce a novel technique to investigate the interactions between R–R intervals and respiratory phases based on their joint symbolic dynamics. To evaluate the technique, electrocardiograms (ECG) and respiratory signals were recorded in 13 healthy subjects in different body postures during spontaneous and controlled breathing. Herein, the R–R time series were extracted from ECG and respiratory phases were obtained from abdomen impedance belts using the Hilbert transform. Both time series were transformed into ternary symbol vectors based on the changes between two successive R–R intervals or respiratory phases. Subsequently, words of different symbol lengths were formed and the correspondence between the two series of words was determined to quantify the interaction between cardiac and respiratory cycles. To validate our results, respiratory sinus arrhythmia (RSA) was further studied using the phase-averaged characterization of the RSA pattern. The percentage of similarity of the sequence of symbols, between the respective words of the two series determined by joint symbolic dynamics, was significantly reduced in the upright position compared to the supine position (26.4 ± 4.7 vs. 20.5 ± 5.4%, p