In this study, an approach based on the analysis of RR Interval data obtained from electrocardiograms (ECG) is presented to distinguish between wake and sleep states. Specifically, APEN (Approximate Entropy) and SampEn (Sample Entropy) entropies are employed. Data were collected from two control groups of patients: one consisting of 83 patients recorded for 24 hours and another of 10 patients recorded exclusively during 8 hours of sleep. A total of 111 comparisons were made between the entropies of the RR intervals of both groups. Preliminary results indicate that there is a significant difference in entropies between awake and asleep patient groups. It was observed that RR interval entropies during sleep tend to be similar to each other and different from those observed during wakefulness. Analysis of p-values revealed significant variability in the comparisons made, ranging between 3,2 × 10−22 and 4,2 × 10−26 These findings suggest that the analysis of RR interval entropies may be a promising tool for distinguishing between wake and sleep states from ECG signals. This approach has the potential to contribute to the development of non-invasive methods for sleep monitoring and early detection of sleep-related heart disorders, also these results can be used to perform the Tilt test in 24 hours.