Development of an ECG-Based Diagnostic System for Report Generation and Signal Analysis

In order to record the electrical activity of the heart and diagnose different cardiac diseases, the electrocardiogram (ECG) is an essential clinical tool. The complete development of an ECG system, from signal capture to waveform analysis, is examined in this study. To eliminate noise and interference, the raw ECG signal is recorded using electrodes and amplification circuits, then processed by digital filters. Key waveform elements like the P, QRS complex, and T waves are recognized by the system in order to understand cardiac activity. Abnormalities like arrhythmia or ischemia are detected using algorithmic analysis and sophisticated processing techniques. It is a hybrid paradigm for real-time cardiac monitoring, with a focus on both software analysis and hardware design. Future research will use AI-based classification and the integration of portable ECG devices to improve accuracy. A significant development in cardiac healthcare, the ECG Report Analysis System was motivated by the urgent need to increase diagnostic precision and effectiveness in light of the rising incidence of cardiovascular disorders. Using cutting-edge technology to provide prompt and accurate diagnostics, our goal is to revolutionize the way cardiac problems are identified and treated. In the current healthcare environment, where every heartbeat matters, our technology uses machine learning and signal processing to transform raw ECG data into insights that can be put to use.