Nonlinear analysis of heart rate variability of healthy subjects and patients with chronic obstructive pulmonary disease

Abstract

Chronic obstructive pulmonary disease (COPD) is one of the causes of mortality worldwide with an increasing prevalence. Heart rate variability (HRV) reflects the regulation mechanism of the cardiac activity by the autonomic nervous system. The assessment of HRV by using nonlinear methods is more sensitive for the detection of complexity when compared to linear methods. This study aims to get information about the autonomic dysfunction occurred in patients with COPD by analysing the complexity of HRV. Electrocardiogram signals recorded from healthy subjects, patients with moderate COPD and severe COPD (eight subjects per group) were analysed. The HRV signals were acquired from ECG signals. Signals were reconstructed in the phase space and largest Lyapunov exponent (LLE), correlation dimension, Hurst exponent and approximate entropy (ApEn) values were calculated. It has seen that for the patients with COPD LLE, correlation dimension, Hurst exponent and ApEn values were less than control group. According to this, HRV complexity decreases in the presence of COPD. However, there is no significant difference between COPD groups and the severity of COPD has no effect on the chaoticity of the system. The results revealed that autonomic dysfunction occurred in patients with COPD is associated with reduced HRV complexity.

Keywords:

• Chronic obstructive pulmonary disease
• heart rate variability
• nonlinear analysis
• phase space reconstruction
• complexity

Disclosure statement

We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.