Title :
Renyi entropy measures of heart rate Gaussianity
Author :
Lake, Douglas E.
Author_Institution :
Cardiovascular Div., Univ. of Virginia, Charlottesville, VA, USA
Abstract :
Sample entropy and approximate entropy are measures that have been successfully utilized to study the deterministic dynamics of heart rate (HR). A complementary stochastic point of view and a heuristic argument using the Central Limit Theorem suggests that the Gaussianity of HR is a complementary measure of the physiological complexity of the underlying signal transduction processes. Renyi entropy (or q-entropy) is a widely used measure of Gaussianity in many applications. Particularly important members of this family are differential (or Shannon) entropy (q=1) and quadratic entropy (q=2). We introduce the concepts of differential and conditional Renyi entropy rate and, in conjunction with Burg´s theorem, develop a measure of the Gaussianity of a linear random process. Robust algorithms for estimating these quantities are presented along with estimates of their standard errors.
Keywords :
Gaussian processes; electrocardiography; entropy; medical signal processing; Burg theorem; Renyi entropy; Shannon entropy; central limit theorem; differential entropy; heart rate Gaussianity; linear random process; quadratic entropy; signal transduction; Entropy; Gaussian processes; Heart rate; Heart rate variability; Lakes; Pediatrics; Probability; Random processes; Signal processing; Stochastic processes; Entropy rate; Gaussianity; Renyi entropy; SampEn; heart rate variability; Algorithms; Arrhythmias, Cardiac; Computer Simulation; Data Interpretation, Statistical; Diagnosis, Computer-Assisted; Electrocardiography; Entropy; Heart Rate; Models, Cardiovascular; Models, Statistical; Normal Distribution; Reproducibility of Results; Sensitivity and Specificity; Severity of Illness Index;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.859782