An introduction to the use of evolutionary computation techniques for dealing with ECG signals

Abstract

Evolutionary Computation (EC) has become one of the most developed and successful computational intelligence techniques used for solving real-world problems from different application areas, including engineering, machine learning, signal processing, and data mining, among many others. It is indeed particularly worth noticing the success of the use of EC techniques for dealing with problems that involve the processing, classification, and interpretation of different sources of signals. From them, the treatment of ECG signals represents a challenge for the scientific community since such a problem has not only a high academic impact, but an important social impact, as well. In this chapter we present an introduction to basic EC concepts, including the description (under a unified perspective) of the most representative algorithms within this area. Furthermore, the chapter is aimed to provide the reader with the fundamentals of the most representative EC-based methodologies and other well-known bio-inspired metaheuristics that have been adopted for dealing with the treatment of ECG signals. Additionally, some areas for future research are also identified towards the end of the chapter.