Development of A Real-Time Embedded System For Cardiac Signal Monitoring And BPM Detection

Cardiovascular diseases are still one of the main causes of illness and death all over the world, which means that it is important to carry out continuous and reliable monitoring of the heart's electrical activity if an early evaluation of heart health is to be made. Electrocardiography (ECG) is one of the most commonly used non-invasive methods for recording the electrical activity of the heart and for detecting changes in heart rate and in the shape of the waveform. On the other hand, the conventional ECG monitoring equipment used in hospitals and diagnostic centres is generally rather expensive, bulky, and not very appropriate for use in portable or continuous monitoring situations. The paper describes the design and implementation of an ECG monitoring system that is low-cost, portable, and capable of real-time operation, the system making use of an Arduino UNO microcontroller and an AD8232 ECG sensor module. It obtains the cardiac electrical signals from the human body by means of disposable surface electrodes which are placed at suitable positions on the body. The weak biopotential signals picked up by the electrodes are fed into the AD8232 module, where they are conditioned by means of amplification and filtering in order to enhance the quality of the acquired ECG waveform and reduce the effect of noise, motion artifacts, and other undesirable signal components. The conditioned analog output from the AD8232 is then connected to the analog input of the Arduino UNO, where it is sampled and converted into a digital form for real-time monitoring. The ECG signal obtained can be displayed using a computer-based serial monitoring interface, allowing the characteristic changes in the cardiac waveform to be observed. The prototype suggested highlights simplicity, portability, affordability, and ease of implementation, and offers an effective means of carrying out real-time acquisition of cardiac signals. The system shows that it is possible to combine biomedical sensors with low-cost embedded technology for use in ECG monitoring. The platform could be improved by adding functions such as heart-rate estimation, automated extraction of ECG features, detection of abnormalities, wireless transmission of data, cloud-based monitoring, and classification of cardiac diseases using machine learning. Thus, the proposed system forms a practical basis for educational purposes in biomedical instrumentation, for initial cardiac monitoring, for portable healthcare applications, and for future remote patient monitoring systems.