IOT Based Heart Monitoring System Using ECG

Heart disease is still the number one killer in the whole world, and thus proper management requires accurate and timely diagnostic methods. The conventional methods of diagnosis, however, most of them rely on the subjective interpretation of electrocardiogram signals, which often result in inconclusive readings leading to further delays in treatment. This paper addresses this need in terms of automated and reliable heart disease classification through deep learning techniques. Heart diseases include a range of conditions in the heart, such as myocardiatis, ventricular ectopic beats, supra ventricular ectopic beats, fusion beats, and many more. The complexity of signals obtained from ECG presents a major challenge in its proper interpretation, not to mention the subjective nature of a manual diagnosis. Heart disease is one of the leading causes of death worldwide and therefore demands swift and accurate diagnostic strategies for proper management.