Multiparametric analysis of HRV signal by linear and nonlinear methods in heart failure patient population

The paper proposes a quantification of heart rate variability signal (HRV) by a multiparametric analysis. The goal is to verify a possible improvement of the diagnostic and prognostic power of the HRV analysis. Conventional indices in time and in frequency domain have been associated with newer parameters based on nonlinear dynamics, such as approximate entropy and α slope of the 1/f spectrum. The study considers HRV signals derived from 24 hours Holter ECG recordings. The population consists of 17 congestive heart failure patients (CHF) and 5 normal subjects. Results show differences in heart rate control inside the CHF group and between normal and CHF patients. The nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures