Design of a secure-cloud remote medical monitoring system using the P-QRS-T electrocardiogram detection algorithm - Khalef, Rostom; Moulahcene, Fateh; Merazga, Ammar (Institute of Advanced Engineering and Science, 2025)
The COVID-19 pandemic has highlighted the limitations of traditional healthcare, resulting in higher mortality rates among children, the elderly, and healthcare workers. This situation has created a pressing need for urgent medical care from healthcare professionals. This paper presents a secure cloud-based remote medical monitoring system that integrates the internet of things (RMMS-IoT) with advanced P-QRS-T electrocardiogram (ECG) detection algorithms to enable real-time, accurate vital sign analysis. The system combines microcontroller devices, wearable sensors, and medical-grade equipment, leveraging hypertext transfer protocol secure (HTTPS) and Blynk bridge cloud technologies to ensure data security and interoperability. The RMMS-IoT system demonstrated high accuracy in monitoring vital signs by comparing its results with data from actual measuring devices, showing errors in body temperature readings below 1% and heart rate (HR) measurements below 2.8%. The algorithm used to detect P-QRS-T features from the ECG exhibited robust performance in differentiating between normal and abnormal ECG patterns in patients, and it achieved an accuracy rate of 90% in ECG classification.