Nonlinear dynamics methods in the analysis of the heart rate variability

Purpose: We analyzed the heart rate variability (RR intervals) by means of nonlinear dynamics methods: Poincaré plot (return map), approximate entropy (ApEn) and detrended fluctuation analysis (DFA). The purpose of this study was the quantitative and qualitative assessment of heart rate variability by means of these nonlinear dynamics methods. Material and methods: The Poincaré plot is a scattergram, which is constructed by plotting each RR interval against the previous one. Approximate entropy describes the complexity and irregularity of the signals. Detrended fluctuation analysis quantifies fractal-like correlation properties of the data. We analyzed two groups of patients: test group A – 15 diabetic children with diabetes type 1 and microalbuminuria and control group C – 24 healthy children. For each patient 24 hour ECG (RR intervals) was recorded. Statistical analysis was performed by means of nonparametric Mann-Whitney test. Results: Return maps of healthy children are mostly very complex. In the case of diabetic children we found torpedoshaped plots. The values of ApEn were lower in diabetic children that indicated more regular heart rate in these patients. DFA method shows also differences between the investigated groups. Conclusions: We concluded that using nonlinear dynamics methods we could quantitatively and qualitatively study the heart rate variability in healthy and diabetic patients.