Symmetrical Compression Distance for Arrhythmia Discrimination in Cloud-Based Big-Data Services

The current development of cloud computing is completely changing the paradigm of data knowledge extraction in huge databases. An example of this technology in the cardiac arrhythmia field is the SCOOP platform, a national-level scientific cloud-based big data service for implantable cardioverter defibrillators. In this scenario, we here propose a new methodology for automatic classification of intracardiac electrograms (EGMs) in a cloud computing system, designed for minimal signal preprocessing. A new compression-based similarity measure (CSM) is created for low computational burden, so-called weighted fast compression distance, which provides better performance when compared with other CSMs in the literature. Using simple machine learning techniques, a set of 6848 EGMs extracted from SCOOP platform were classified into seven cardiac arrhythmia classes and one noise class, reaching near to 90% accuracy when previous patient arrhythmia information was available and 63% otherwise, hence overcoming in all cases the classification provided by the majority class. Results show that this methodology can be used as a high-quality service of cloud computing, providing support to physicians for improving the knowledge on patient diagnosis.

I. Introduction

Cardiovascular diseases are the primary cause of death worldwide, and they remain directly or indirectly responsible for more than 30% of reported deaths [1]. Arrhythmias are common cardiac conditions in which the contraction rate of the heart is abnormally fast, slow or irregular, usually resulting in an abnormal mechanical function of the heart. Typically, physicians classify arrhythmias into two classes, namely, supraventricular (with atrial origin and usually nonfatal), and ventricular (severe arrhythmias originated at ventricles). Based on their mechanisms and origin, fast arrhythmias are further classified into monomorphic tachycardias (ventricular or supraventricular), flutter (either atrial or ventricular), and fibrillatory rhythms (atrial and ventricular fibrillation) [2].