Backend of Heart Rate Detection System with Early Warning for Patients with Heart Disease

Heart disease remains a leading cause of mortality globally, necessitating effective monitoring and early warning systems for patients at risk. This paper presents the development of a robust backend system for heart rate detection with an early warning mechanism using the Laravel framework, MAX30100 and MLX90614 sensors, and MySQL database. The system integrates an Internet of Things (IoT) approach to continuously monitor and store patient data, including heart rate, oxygen saturation (SpO2), and body temperature. A web-based dashboard and mobile application provide healthcare providers and caregivers with real-time access to this data. Comprehensive load testing evaluated the system's performance under varying user loads. The results indicated a reliable performance with an average response time of 735 milliseconds at 20 Virtual Users (VUs). However, error rates increased under higher loads, highlighting the need for further scalability improvements. The comparative analysis demonstrated the system's competitive edge in accuracy and responsiveness, particularly its early warning feature that alerts caregivers of potential health issues. This study addresses key limitations of existing heart monitoring devices, such as the inability to store continuous data and the lack of remote monitoring capabilities. The proposed system's API integration and real-time data visualization enhance its practical applicability in clinical settings. Future work will optimize system scalability and resilience to manage larger datasets and higher user loads effectively.