IoT-Enabled Arrhythmia Detection using RNNs for ECG Analysis

In today's era, where major changes are taking place in Healthcare Systems, further details on heart diseases have to be regularly provided with emphasis on the management and preventative strategies for arrhythmias in particular. The current study addresses a research problem on whether it is possible to use the data obtained from ECG to make predictions about the presence of heart diseases, especially arrhythmia using machine learning techniques. Arrhythmia is an abnormal heart rhythm where the heart beats too fast or too slow or becomes random without self-identifying and this can be life- threatening if not diagnosed within the right period. This system aims at predicting electrical activity that leads to arrhythmia through the analysis of the ECG signal so that the medical professional is notified in good time for appropriate action. In this study, the authors” of the article will design, implement and evaluate the machine learning-based methods of disease prediction with the ultimate goal to enhance the sensitivity and specificity of cardiac disease predictive diagnostic services.