Design of hospital IoT system and drug intervention in patients with acute myocardial infarction

Abstract Acute Myocardial Infarction (AMI) is a leading cause of death and is a worldwide disorder, despite significant progress in diagnosis over the past decade. AMI is a multifactorial disease that is thought to be due to the interaction of genetic and environmental factors. It requires a high degree of knowledge and experience together to predict acute myocardial infarction is a complicated task. Internet of things (IoT) technology, the Internet, the sensor value of the collection for the diagnosis, and prediction of heart disease, have been adopted in the current medical system. To resolve this problem, it has been proposed to evaluate acute myocardial infarction using a more accurate qualified Quick Decision Diagnosis (QDD) algorithm, the IoT of the framework. Smart wearable device and heart monitoring devices have been attached to the patient's monitoring of blood pressure and Electrocardiogram (ECG). QDD is used to classify the sensor data with the received patient's normal and abnormal data. The simulation results show that the QDD-based myocardial infarction prognosis system is better proposed than other methods offered.

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