Electrocardiogram (ECG) is an effective way to define the overall human health status using the heart activity of the patients in real-time basis. One of the challenges in this field is to have a real-time monitoring system for ECG signals in order to define normal and abnormal ECG signals. This solution helps to detect deteriorating patients in the intensive care units (ICU) to prevent further serious problems. This topic is to provide a solution for ECG signal processing to detect anomalies in the ECG signals using AI for signal processing. The main idea is to collect different types of ECG leads, teach it for an AI model, and then use it to generate the formal shape of every type and then detect anomalies by comparing the built model with the input data. The full design of the software together with the workflow starting from the state of the art, requirement specification, design, to the implementation and testing should be well-defined.