Age and Changes in Extracted Features of Lagged Poincare Plot

Abstract

The Poincare plot is a geometrical representation of RR time series constructed by plotting successive RR intervals on a 2D phase space. In this article, the impact of age on the shape of Poincare plot of RR intervals and extracted features for quantification of this space is considered. Fantasia database from Physionet databank is used in this paper. Two hours of ECG recording (sampling frequency: 250 Hz) for twenty young (21-34 years old) and twenty older adults (68-85 years old) were used while all subjects remained in a resting state. After extraction of RR intervals from ECG, Poincare plot with 10 different lags (1-10) were constructed for each RR series, and eleven different features were extracted for each lag. Extracted features from lagged Poincare plot were used as input to K-nearest neighbor classifier to discriminate between two groups of young and older adults. Sensitivity of 86.5%, specificity of 95.1%, and the accuracy of 91.4% was achieved in the classification.