The purpose of the study was to determine the dependency of the statistical properties of the R to R interval (RRI) time series on progressive central hypovolemia with lower body negative pressure. Two data-processing techniques based on wavelet transforms were used to determine the change in the nonstationary nature of the RRI time series with changing negative pressure. The results suggest that autonomic neural mechanism driving cardiac interbeat intervals during central hypovolemia go through various levels of multifractality, as determined by Hölder exponent distributions.