There are several nonlinear signal processing methods which can be used in cardiovascular studies to characterize heart rate dynamics This paper presents an overview of three different methods to quantify bio signal complexity, especially Heart Rate time series’ dynamics. These are the Kolmogorov complexity, the Sample Entropy and the Permutation Entropy. The proposed methodology contains the estimation of these three parameters for six signals of different lengths and different characteristics. The used signals are Heart Rate Variability time series obtained from specially created databases. The mentioned parameters are computed, analyzed and compared; conclusions are drawn. Measuring the complexity of time series, usually means to find randomness, unrevealed dynamics or deterministic trends in behavior. The experimental results prove the applicability of this methodology in analyzing heart rate time series, but the decisions based on their complexity should be made only by specialists.