ECG Diagnosis for Cardiovascular Diseases Using Soft Computing Algorithms

Abstract

Electrocardiogram (ECG) is widely used in the healthcare domain because of its usage as a diagnostics tool for several cardiovascular diseases. It becomes essential to study and analyse the ECG data with the help of classification techniques. In this review paper, a brief overview of ECG signal information is presented. Various approaches for diagnosing cardiovascular diseases have been discussed, along with the need for accurate ECG signal analysis. These approaches are mainly based on the principles of machine learning and deep learning. The advantages and limitations of these techniques in the detection of cardiovascular diseases are presented within the scope of future work. This study can be helpful for researchers in bridging the gap between current approaches and future techniques for the detection of arrhythmia conditions.