# Electrocardiographic Fragmented Activity (II):
## 1 Introduction  
The heart is the principal element in the circulatory system and it is divided in four chambers--the right and left atria, which are at the upper part of the heart; and the right and left ventricles, which are located at the lower part of the heart. The right part of the heart is responsible for receiving un-oxygenated blood from the whole body and carrying it to the lungs to oxygenate it, whereas the left part is responsible for receiving the oxygenated blood from the lungs and sending it to the whole body. This process is performed by the heartbeat, which is originated in the sinoatrial node, a small mass of tissue located in the right atrium. This node acts as a pacemaker creating the basic electrical impulse that travels to the atrioventricular node, which is a mass of tissue located between the atria and the ventricles. In this node, the impulse is delayed allowing the blood flowing from the atria to ventricles. Finally, this impulse is conducted to the His bundle where it is divided in two paths, in order to reach both ventricles simultaneously [1]. In terms of a representation of real electrical activity and operational behavior of the heart, the electrocardiogram (ECG) has proven to be the most widespread used tool for fast heart functioning diagnose. This test consists of several electrodes attached to the patient chest and limbs which record the different projections of the cardiac electrical activity. It allows clinicians to easily detect a wide number of illness, such as, abnormalities in rhythm like tachycardia or bradycardia, abnormalities in electrical conduction like bundle branch blocks, or markers of sudden cardiac death, among others [2,3]. In this work, we covered the fibrosis, which is the apparition of non-conductive (fibrous) tissue patches among the normal myocardium tissue. These patches act as obstacles in the normal myocardium electrical conduction and favor the risk of suffering different kinds of arrhythmias [4], even those ones that cause sudden cardiac death. On the other hand, recent research [5, 6, 7] suggested that the presence of fragmentation, which is a ECG feature manifesting as a number of extra peaks and deflections in QRS complex, is related to the presence of myocardial fibrosis. Nowadays, the fragmentation is detected by visual inspection of the ECG and this method presents two main drawbacks, namely, several different definitions of this condition are present in the literature and the inter-observer error is high, because this characteristic can be confused with noise or artifacts in the ECG. On the other hand, the fibrosis is detected by magnetic resonance imaging with late gadolinium enhancement (MRI-LGE), which is an expensive test in terms of time and money. Therefore, the main objectives of this work are two, namely, the development of an algorithm allowing a systematic detection of fragmentation in the ECG and the evaluation of the detection power of these very same techniques to identify the visually unnoticeable effects of fibrosis on digital registers. In the companion paper [8], we scrutinized the behavior of two frequently used multivariate transforms, principal component analysis (PCA) and independent components analysis (ICA), over a fragmented subrogated model of ECG. As a result, this previous work proved that the use of these transforms can enhance the presence of fragmentation waves in the computed components. In this work we extend the use of these transformations in order to compute features that can be used in a classifier for the suitable fragmentation and fibrosis detection.