Wearable Patient Monitor Based On ESP-Now And Web (ECG Lead II, BPM, SpO2, RR, NIBP,Skin Temperature, Website)

The advancement of wearable health technology has enabled the development of compact and wireless systems for real-time monitoring of vital signs, improving accessibility and patient comfort in various healthcare scenarios. This study presents the design and implementation of a wearable patient monitoring system capable of continuously measuring electrocardiogram (ECG Lead II) signals and calculating heart rate (BPM) using the AD8232 analog front-end sensor, which is interfaced with the low-power ESP32-C3 XIAO microcontroller. The captured biopotential signals are transmitted wirelessly via the ESP-NOW communication protocol to a centralized master unit without requiring standard Wi-Fi connectivity, ensuring low latency and energy efficiency. The physiological data are then visualized in real time through a web-based dashboard and an integrated Nextion LCD touchscreen, enabling both remote and local monitoring. In addition to heart rate and ECG, the system is equipped with a MAX30102 optical sensor for measuring peripheral oxygen saturation (SpO₂), and a piezoelectric sensor combined with a signal conditioning circuit for capturing respiratory rate (RR). Non-invasive blood pressure (NIBP) measurement is performed using the oscillometric method, facilitated by the MPX5100GP pressure sensor controlled via a Wemos D1 Mini microcontroller. Each module functions autonomously, allowing scalable and modular integration of multiple biosignal parameters. The entire system operates on battery power, enhancing its portability and usability in both clinical and home-based environments. Performance evaluations demonstrate that the system provides accurate physiological readings with minimal error when compared to clinical references. Its wireless, wearable, and modular architecture makes it particularly suitable for continuous patient health tracking, early detection of abnormalities, and personal health data logging. Overall, the proposed system shows significant potential to support modern telemedicine applications, especially in situations that demand flexible, real-time, and reliable multi-parameter monitoring solutions.