Do-it-yourself Electrocardiogram DIY-ECG скачать в хорошем качестве

Do-it-yourself Electrocardiogram DIY-ECG

In this project, a fully open-source do-it-yourself electrocardiography system - in short DIY-ECG- is presented. It was developed specifically for teaching medical engineering students how real biosignal acquisition actually works — from electrode placement and microvolt-level amplification to digital filtering, signal processing, and visualization. Electrocardiography measures the electrical activity of the heart. The heart can be modeled as a time-varying electrical dipole whose magnitude and orientation change during each heartbeat. This activity is measured as a potential difference between two electrodes, for example at the left and right wrist, while a third reference electrode improves signal stability and reduces noise.. The most prominent feature of the ECG signal is the R-peak, which marks each heartbeat. The time interval between successive R-peaks determines the heart rate. A key component of the project is the analog front-end: a simple and transparent design based on an inexpensive quad operational amplifier. Instead of using a ready-made instrumentation amplifier module, the circuit is implemented as an Arduino shield and soldered by the students themselves. This hands-on approach makes the electronics interface more understandable. The first version was built around the Arduino Uno. The conditioned ECG signal is sampled and streamed to a computer, where digital filtering, adaptive R-peak detection, and visualization were implemented in GNU Octave. A major step forward came with the introduction of the Arduino Uno Q. It offers the unique opportunity to build a fully standalone ECG system without the need for an external computer. Therefore the original Arduino C++ and Octave-based workflow had to be migrated to the Uno Q architecture. On the MCU side, real-time acquisition runs under Aruino C++/ Zephyr. On the MPU side, a Linux-based Python environment (inside a Docker container) handles higher-level processing and data management. The ECG data are forwarded to a WebUI providing real-time visualization using HTML, JavaScript, and WebGL. The browser can run directly on the Uno Q itself — currently using Chromium on XFCE or Firefox within a Weston Wayland compositor. The standalone Uno Q setup, combined with a 15.6-inch HDMI monitor and powered via a power bank, significantly reduces power-line interference while improving electrical safety. A custom-designed 3D-printed holder integrates the components into a compact and robust teaching device. The project demonstrates how Arduino can evolve from a simple microcontroller platform into a fully integrated biomedical teaching device — combining analog signal conditioning, real-time embedded processing, Linux-based software architecture, and browser-based visualization in one coherent system.