- No Installation Required: Simply plug and play on any machine with a web browser.
- Cost-effective: The device costs less than £15.
- Local Data Processing: All data is processed locally, ensuring regulatory compliance and enhanced privacy.
- Three Measurement Modes: Provides enhanced diagnostic capabilities through multiple measurement modes.
- Backed by NeuroKit2: Utilizes the well-established NeuroKit2 Python library for robust analysis. Plots BPM variation and the mean PQRST cardiac cycle.
- High Sampling Frequency: Sampling frequency of 2.3kHz far exceeds the recommended 250 Hz for accurate cardiac analysis.
- Low CPU Usage: On average, uses less than half a thread when continuously plotting 5,000 data points at 60FPS.
- Responsive UI: Includes spinners, status bars, and dynamically enabled buttons for a smooth user experience.
By using a web interface for our ECG, we have many inherent advantages. Updates can be issued frequently and remotely, leading to future potential for subscription-based services/integrations with telehealth platforms. In our case, since all data is processed locally, we don't pay for any web hosting costs!
- Build the Hardware: Check out the KiCad schematic files in the
hardware/directory. - Flash the Firmware: Open the Arduino IDE in the
firmware/directory, or download precompiled binaries from the releases tab. - Visit Our Platform: Access the web application at sf4-data-logger.netlify.app.
- Connect the Hardware: Plug in the ECG device to your computer.
- Start Measuring: Begin taking measurements and analyzing data instantly through your web browser.
