Connected Health in Action: An IoT-Driven Web Dashboard for Real-Time HRV and Stress Monitoring in a Private Cloud - José, Moser Zeferino Vicente; Mutter, Pedro de Almeida; Estrella, Julio Cezar (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia); 2025: Proceedings of the 31st Brazilian Symposium on Multimedia and the Web, 2025)
Stress is one of the main factors associated with the worsening of cardiovascular diseases and psychological disorders, with Heart Rate Variability (HRV) being one of the most widely used physiological indicators for its detection and monitoring. This work proposes the development of a continuous stress monitoring architecture based on the Internet of Things (IoT), using the Polar H9 heart rate sensor connected via Bluetooth Low Energy (BLE) to an embedded processing unit based on the Raspberry Pi 4. The system performs real-time acquisition and transmission of heart signals through Python-based scripts. Communication with the private cloud is handled via the RabbitMQ, and data visualization is implemented through a web dashboard accessible via WebSocket, enabling continuous and multiplatform monitoring. The architecture was designed to extract classical HRV metrics, such as RMSSD, SDNN, and pNN50, which are collected from the R-R intervals transmitted by the system. The results obtained demonstrate that the architecture is capable of capturing, processing, and transmitting these metrics with high stability, providing a solid foundation for applications in HRV analysis and stress indicators. Future work will focus on integrating machine learning models for automatic stress classification and conducting clinical validation with multiple participants to enhance the system’s reliability and applicability.