Bootstrapping the empirical bounds on the variability of Sample Entropy in 24-hour ECG recordings for 1 hour segments

We investigate the variability of one of the most often used complexity measures in the analysis of the time series of RR intervals, i.e. Sample Entropy. The analysis is carried out for a dense matrix of possible r thresholds in 79 24h recordings, for segments consisting of 5000 consecutive beats, randomly selected from the whole recording. It is repeated for the same recordings in random order. This study is made possible by the novel NCM algorithm which is many orders of magnitude faster than the alternative approaches. We find that the bootstrapped standard errors for Sample entropy are large for RR intervals in physiological order compared to the standard errors for shuffled data which correspond to the maximum available entropy. This result indicates that Sample Entropy varies widely over the circadian period. This paper is purely methodological and no physiological interpretations are attempted.