Published Paper Details:

This project focuses on designing and building a compact, multi-parameter biomedical monitoring system using the ESP32 microcontroller. The idea behind this work was to create a simple, low-cost device that can continuously track important health parameters, especially in situations where access to advanced medical equipment is limited or not practical. To achieve this, the system combines several commonly used biosensors. A MAX30102 module is used to measure heart rate and blood oxygen levels (SpO?) using photoplethysmography (PPG). For monitoring heart activity, an AD8232-based ECG sensor is included, while muscle signals are captured using a basic EMG sensor. In addition, a temperature sensor such as the DS18B20 is used to keep track of body temperature. Bringing all these sensors together allows the system to monitor multiple physiological signals at the same time. Both analog and digital signals from these sensors are handled by the ESP32. For signals like ECG and EMG, which are more sensitive to noise, simple signal conditioning techniques were applied. This included basic amplification and RC filtering to reduce interference from sources like power-line noise and body movement. The ESP32 reads these signals through its ADC channels, while digital data from the MAX30102 is obtained via I2C communication. Depending on the type of signal, a sampling rate between 100 and 500 Hz was used. To further improve signal quality, lightweight software filters such as moving average and bandpass filters were implemented. The system is capable of processing multiple inputs almost in real time, with reasonable synchronization across different channels. The measured values--such as heart rate (in BPM), SpO? levels, ECG waveform, EMG activity, and temperature--are displayed instantly on a small LCD or OLED screen. This makes it easy to view the data directly on the device without needing any external system. To extend its functionality, the ESP32's built-in Wi-Fi is used to send data to cloud platforms like Thing Speak or through an MQTT-based setup. This allows users or healthcare providers to monitor the readings remotely from anywhere with an internet connection. The communication is designed to be lightweight so that it does not significantly affect performance or power consumption. One of the main strengths of this system is its affordability and simplicity. Since it uses easily available components, the overall cost remains low, making it suitable for home monitoring, educational projects, or basic telehealth applications. Data transmission to the cloud was also reliable, with only minor delays observed. However, it is important to note that this system is intended as a proof-of-concept and is not a replacement for certified medical equipment. Overall, this project demonstrates how microcontrollers like the ESP32, when combined with low-cost sensors and IoT capabilities, can be used to build practical and accessible health monitoring solutions.