Novel Techniques of Detecting Arrhythmia using Artificial Intelligence Techniques

Abstract

Abstract: The study shows that many computer programs using AI have been made to look at the ECG signal and find heart problems. We need to find and treat cardiac diseases early these days if we don't want them to happen. With the help of new technology in health informatics that gathers, sorts, and finds data, there may be new ways to avoid CVDs. Using AI-based methods, it is possible to correctly sort ECG data to find tachycardia. There are several steps in the process of classifying. It is easier for a convolutional neural network to find rhythms. But the health care system still needs to use smart tech to always check on people's heart health. The experts have found some issues in this area. You need better tools to do a great job of analysing ECG data. Sometimes these computer methods don't work right, but they are becoming very helpful for making medical progress. In the field of heart electrophysiology (EP), simple AI have been used for many years. Deep learning techniques are becoming more common once more. This has led to new discoveries in electrocardiography research, like being able to tell when someone is sick by looking at their signature. AI is getting better, and computers, devices, and websites are getting better quickly. This has led to the fast growth of AI-enhanced apps and big data studies. New ways of living, the rise of the internet of things, and better phone systems have made it easier to find people in a community who have atrial fibrillation than it was before. AI has made it possible to get better 3D images of the heart, which led to the idea of virtual hearts and models of heart beats.