Detection of anomalous events in biomedical signals by wigner analysis and instant-wise Rényi entropy

Rényi entropy is receiving an important attention as a data analysis tool in many practical applications, due to its relevant properties when dealing with time-frequency representations (TFR). Rényi entropy is characterized for providing generalized information contents (entropy) of a given signal. In this paper we present our results from applying the Rényi entropy to a 1-D pseudo-Wigner distribution (PWD) of a biomedical signal. A processed filtered signal is obtained by the application of a Rényi entropy measure to the instant-wise PWD of the given biomedical signal. The Rényi entropy allows individually identify, from an entropic criterion, which instants have a higher amount of information along the temporal data. Our method makes possible accurate localization of normal and pathological events in biomedical signals; hence early diagnosis of diseases is facilitated this way. The utility of our method is illustrated with examples of application to phonocardiograms.