Biomedical Sensing and Real-Time Wireless ECG Acquisition with STM32

Background

Biosignal acquisition forms the foundation of many biomedical monitoring, wearable sensing, and human–machine interface applications. Physiological signals such as electrocardiography (ECG), electromyography (EMG), electroencephalography (EEG), and electrodermal activity provide valuable information about the electrical and functional state of the human body. However, reliable acquisition of these low-amplitude signals requires careful consideration of electrode–skin contact, analog front-end design, signal conditioning, sampling, noise rejection, and electrical safety. Recent advances in low-power microcontrollers, integrated analog front ends, and wireless communication have made it possible to develop compact and portable biosignal monitoring systems using readily available embedded platforms. These developments create an excellent opportunity to combine fundamental biomedical instrumentation concepts with practical embedded-system implementation in a hands-on learning environment. The symposium, which serves as a specialized session of the 5th International Conference on Modern Medicine and Global Health (ICMMGH 2027), will focus on biology and biomedicine.

Goal/Rationale

The goal of this symposium is to provide participants with a practical understanding of the complete biosignal acquisition chain, from the physiological source to real-time digital visualization. While biosignal processing is frequently introduced at the software level, the quality and reliability of physiological measurements are strongly influenced by earlier stages including electrode placement, analog conditioning, sampling strategy, and embedded data acquisition. The symposium will address this gap through a practical ECG-based implementation.

STM32 is selected as the embedded platform because of its widespread use in academic and industrial applications, flexible analog-to-digital conversion capabilities, hardware timers, DMA support, low-power operation, and suitability for deterministic real-time data acquisition. These features make it particularly appropriate for demonstrating how physiological signals can be sampled and processed efficiently in resource-constrained embedded systems.

Participants will first be introduced to the basic principles of biopotential measurement, differential acquisition, common-mode interference, signal conditioning, sampling, and motion-related artifacts. ECG will then be used as a representative biosignal to demonstrate a complete real-time acquisition system. An STM32-based platform will acquire the conditioned ECG signal, organize the samples into data packets, and transmit them wirelessly to a computer, where the waveform will be reconstructed and displayed in real time. The symposium therefore connects biomedical instrumentation, embedded programming, wireless communication, and basic physiological signal processing within a single practical workflow.

Scope

The symposium is intended for students, researchers, engineers, and developers interested in biomedical instrumentation, embedded systems, wearable technologies, physiological monitoring, and digital health. No advanced prior experience in biosignal acquisition is required, although basic knowledge of electronics or programming will be beneficial.

The hands-on activities will cover:

• fundamentals of biosignal and biopotential acquisition;
• ECG electrodes, electrode–skin interface, and measurement configurations;
• analog front-end concepts, amplification, filtering, and noise reduction;
• STM32-based ADC configuration and real-time sampling;
• timer-driven acquisition, buffering, and data handling;
• wireless transmission of physiological data;
• PC-side reception and real-time ECG visualization;
• identification of common noise, motion artifacts, and acquisition limitations;
• basic extraction of physiological information such as R-peaks and heart rate.

By the end of the symposium, participants will have experienced the complete path from a physiological electrical signal on the body to its real-time wireless visualization on a computer.