Algoritmo de detecção da fibrilação ventricular

Abstract

The technological development achieved by society has contributed to profound changes in the way of life, giving greater comfort to daily activities. On the other hand, technological use in several activities has led to a sedentary lifestyle, consequently increasing associated diseases, such as respiratory, chronic diseases, diabetes, cardiovascular diseases and high levels of stress. In the case of cardiovascular diseases, which is one of the main causes of death in the world, it is worth highlighting the pathology of ventricular fibrillation. This pathology is an arrhythmia, in which its waves have frantic ties that cause the ventricular muscle to contract in a chaotic way. In Brazil, the Unified Health System (Sistema Único de Saúde), the SUS, despite numerous achievements, still presents limitations that compromise the agility and quality of the services provided to the population. Thus, it is necessary to develop research for the creation of technological innovations that allow greater efficiency in serving the population, avoiding the long distances. This can be observed through the initiatives of telehealth and tele-education, which aim to improve the quality of assistance to the basic services of SUS, and to provide a form of distance education. The objective of this research is to develop an algorithm capable of detecting Ventricular Fibrillation (FV) through the use of the Discrete Wavelet Transform (TWD), thus, for the generation of a rapid pre diagnosis in people who have this cardiac pathology. For that, a qualitative and quantitative data approach was adopted, in which the following methodological instruments were used: state of the art, methodological theoretical survey, and use of the discrete wavelet transform for the ventricular fibrillation signal analysis. From the development of the algorithm, it can be noted that the tool has some limitations regarding sensitivity and predictability (parameters of analysis), which directly interfere with its ability to generate a rapid pre-diagnosis for the identification of Ventricular Fibrillation.