Abstract
Electrocardiography (ECG) has long been a common method of assessing and diagnosing cardiovascular problems (CaDs). The heart’s electrical activity is visualized in the form of a waveform and its analysis can turn out to provide valuable insights about the functioning and normalcy of a healthy heart or detect a wide range of possible heart risks. This article deals with the Internet of Medical Things (IoMT) based real time healthcare monitoring system which diagnoses the ECG signals remotely and hence manifests essential heart conditions. An electrocardiograph machine captures medical-grade patient heart data. The outcome of the project includes detecting the heart rate, the various interval and segment analysis of the signal, cardiac axis detection as well as prompting the various possible conditions in case of anomalies in the heart activities. In such cases, the system can send an automatic ECG report from the patient to the doctor safely by encrypting this report. It can be further modified to generate a call in case of critical condition and provide urgent medical assistance. During the ECG analysis, the article presented clearly results represented by finding different values for different patients starting from QRS width 96, PR Interval 133, and P amplitude 2.81, and ending last patient test QRS width 93, PR Interval 112, and P amplitude 1.57.
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