Problem

We faced the challenge of reliably acquiring biomedical signals in a compact laboratory setup. Instrumentation in Biology and Medicine demands precise amplification to extract meaningful waveform data from small bioelectrical signals, which is sensitive to noise and drift. Calibrating the amplifier chain with both AD620 instrumentation amplifiers and LM324 support was essential to ensure fidelity across varying signal conditions.

We needed a workflow that could validate the system end-to-end and provide real-time feedback to researchers. The lack of an integrated environment for waveform sampling and visualization often slowed iteration cycles and made troubleshooting more difficult. By establishing clear calibration targets, we aimed to reduce measurement uncertainty and accelerate prototyping of biomedical sensing circuits.

Solution

We integrated an Arduino MKR Zero microcontroller to enable real-time data acquisition from the amplifier stack, ensuring low latency and synchronous sampling. The system was designed to support calibration routines for the AD620 instrumentation amplifier and accompanying LM324 stages, enabling consistent gain and offset adjustments across test signals.

To streamline analysis, we deployed Jupyter Notebook workflows for waveform sampling and visualization, capturing essential metrics such as gain accuracy, noise floor, and bandwidth. This combination allowed us to iterate quickly on hardware tuning and validate performance with repeatable experiments, ultimately producing a robust signal acquisition chain for biomedical experiments and educational demonstrations.

PQRST waveform

Fourier Transform of waveform

EKG Circuit