Evaluation and Categorization of ECG Signal for Arrhythmia Detection with CNN - AlexNet

Heart arrhythmia is indeed an irregular heartbeat caused by improper electrical signals in the heart. Some of these irregular heartbeats are harmless, while others can be very serious or even life-threatening. These irregular heartbeats can lead to symptoms that affect our ability to function properly. Arrhythmias are becoming more common worldwide due to modern lifestyles and dietary habits. China, India, Russia and the United States have seen maximum numbers of cardiac disease deaths. This emphasizes the importance of early diagnosis to prevent fatal outcomes. One common method of diagnosing arrhythmia is using an Electrocardiogram (ECG). However, the visual inspection or interactive analysis through ECG may not be very effective. To improve accuracy, efficiency, and speed in diagnosis, an enhanced methodology is proposed here. This includes using more appropriate parameters like the QRS complex and heartbeat rate, and combining them with a CNN (Convolutional Neural Network) model. This combination could potentially provide better standards for detecting arrhythmias. By enhancing the detection process with these improvements, the approach could provide a valuable contribution to the medical field in detecting and diagnosing arrhythmias more effectively. This will potentially be a significant advancement in improving healthcare and preventing serious heart-related issues.