The COVID-19 pandemic has shown the significance of remote patient monitoring in ensuring the safety of both patients and doctors. Simultaneously, the growth of the internet in medical applications has proven its effectiveness in remote data acquisition and monitoring. These types of systems also have their implication in the rural health care centers, which can ensure the monitoring of patients by doctors and paramedics from distant areas. This study proposes a low-cost, low-energy patient monitoring system to gather different vitals such as Electrocardiogram (ECG), heart rate, blood Oxygen saturation level (SpO2), body temperature and to send these data to the doctor via the internet. The system sends an alert message to healthcare providers locally using a GSM module in case of critical condition. A web application was created to facilitate communication between the physician and the patient. The web application is also equipped with Deep learning-based arrhythmia detection feature from the acquired ECG data and pneumonia detection from chest X-rays. The system also facilitates remote monitoring to serve remote areas with no or inadequate healthcare facilities and physicians. Thus, will aid tele-healthcare. © 2021 IEEE.
IoT-Based Low-cost Remote Patient Monitoring and Management system with Deep Learning-Based Arrhythmia and Pneumonia detection