The analysis of heart rate variability (HRV) is based on the study of changes detected in each cardiac cycle. These changes have been studied from the cardiac rhythm signal and it is composed of data acquired from the time measured between the R waves of electrocardiographic signal. The cardiac rhythm signal analysis is based on two kinds of methods: statistical calculation (time domain) and the power spectrum density estimation (frequency domain). Power spectrum density (PSD) estimation from cardiac rhythm signal, can be done through math methods for signals with non-regular sampling time. For this case, in the literature has been registered the use of Lomb method. The main goal of this paper is the presentation of results obtained from the implementation of a technical based on spectrum averaging oriented to ripple decrease of the PSD estimation in cardiac signal rhythm. The final procedure is based on the application of the same technique taking cardiac rhythm signals acquired from normal sinus rhythm database “Physionet”. The results obtained from these experiments showed a decrease of ripple in the PSD and variation of parameters in the frequency domain.