Influence of embedding dimension on distribution entropy in analyzing heart rate variability

Abstract

Distribution entropy (DistEn) is a recent measure of complexity that is used to analyze Heart Rate Variability (HRV) data. DistEn which is a function of data length N, number of bins M and embedding dimension m is known to be stable and consistent with respect to parameters N and M respectively. Also, (N, M) are known to have a combined effect in deciding performance of DistEn as a classification feature. But, all such analysis have mostly ignored the influence of the third parameter m on DistEn properties. Though a random fixed choice of m value has so far succeeded in portraying the effect of other parameters on DistEn, it is considered equally important to reveal the influence of a varyin..