Detection of Events in Biomedical Signals by a Rényi Entropy Measure

Abstract

Biomedical signals contain important information about the healthy condition of human beings. Anomalous events in these signals are commonly associated to diseases. The information content enclosed by time‐frequency representations (TFR) of biomedical signals can be explored by means of different Renyi entropy measures. To be precise, Renyi entropy can be approached under different normalizations, producing different outcomes. The best choice depends upon the particularities of the application considered. In this paper we propose a new processing scheme to the problem of events detection in biomedical signals, based on a particular normalization of the Reny entropy measurement. As in the case of another TFR’s, the pseudo‐Wigner distribution (PWD) of a biomedical signal can take negative values and thus it cannot be properly interpreted as a probability density function. Therefore a complexity measure based on the classical Shannon entropy cannot be used and a generalized measure such as the Renyi entropy ...