Disorder classification in the regulatory mechanism of the cardiovascular system

Abstract

An approach to classify disorders in autonomic control of cardiovascular system is proposed in this paper. The target of this study is to highlight main features of malfunctions in cardiovascular system due to autonomic disorder. Collecting the data from the physionet archive, we divide patients into two groups of normal and abnormal, based on having autonomic disorder in their cardiovascular system or not. Systolic blood pressure (SBP) and heart rate (HR) time series are evaluated for each patient. We then plot the diagram of SBP against HR for all patients in a single figure. Fuzzy c-means clustering (FCM) method is also applied to cluster data into two groups. A neural network is then implemented to classify and to distinguish the two groups. The network is trained with data of a normal patient and is tested with data of other normal and abnormal patients. Result show that selected features can clearly detect disorders in autonomic system.