Analysis of age-related heart rate variability using fuzzy entropy

The aim of this investigation was to determine the fuzziness values of the variables that represent heart rate variability (HRV) for three age groups, using the fuzzy entropy function. We used one hundred and four waves taken from one-minute electrocardiogram (ECG) of males subjects 20-69 years old, this being a short-term HRV measure. In the time domain, the values of the variables SDNN, HR, STDHR, RMSSD, NN50, PNN50, Triangle, TINN, were calculated. In the frequency domain, spectral analysis of continuous power was conducted, quantifying the following powers: very low frequency (VLF,0-0.04 Hz), low frequency (LF, 0.04 to 0.15 Hz), high frequency (HF, 0.15-0.4 Hz ), and the ratio of LF to HF (LF/ HF) . The existing literature on the subject states, that the three frequency bands into which the total power is divided are similar regardless the age, sex and the presence or absence of coronary disease. In the nonlinear domain the values of the variables SD1 and SD2, which describe short and long-term variability were calculated. Measures of the selected patients were taken in the evening after 10 minutes rest. Then the linguistic variables and linguistic terms were defined and such variables were fuzzyfied using triangular and trapezoidal fuzzy numbers. All the variables values in the proposed conditions, satisfy the property that HRV decreases with age. Then the fuzziness of the linguistic terms was analyzed using the continuous fuzzy entropy thus concluding that the variables in the time, frequency and non-linear domains: SDNN, RMSSD, NN50, PNN50, LF, HF, SD1, SD2 corresponding to the first and second age group have the greatest disorder.