SF4-Data-Logger: A Web Based ElectroCardiogram (ECG)

Features

• 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!

Try It out

1. Build the Hardware: Check out the KiCad schematic files in the hardware/ directory.
2. Flash the Firmware: Open the Arduino IDE in the firmware/ directory, or download precompiled binaries from the releases tab.
3. Visit Our Platform: Access the web application at sf4-data-logger.netlify.app.
4. Connect the Hardware: Plug in the ECG device to your computer.
5. Start Measuring: Begin taking measurements and analyzing data instantly through your web browser.

Screenshots