The most recently introduced concept of a `complete entropy profile' is a non-parametric (with regard to tolerance r) approach of entropy estimation. Given a signal, on generating its complete entropy profile, numerous secondary measures of regularity can be derived from the same. These profile based measures are seen to outperform the traditional ApEn statistic (evaluated at a single r) in estimating signal regularity. In this paper, we compare the performance of ApEn (evaluated at an r = 0.15 * SD of signal and an m = 2) with that of profile based measures such as MaxApEn, TotalApEn, AvgApEn, SDApEn, kurtApEn and skewApEn, in detecting `Arrhythmic' RR interval signals from `Normal' RR interval signals. Results indisputably prove the superiority of AvgApEn (AUC > 0.9 at data lengths N ≥ 200) and MaxApEn (AUC > 0.75 at all data lengths) as regularity statistics in detecting Arrhythmia, above all the other measures used.