Open-Source, High-Speed and High-Resolution Data Acquisition Platform for Biopotential Recordings and Neural EIT applications
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Objective
Biopotential measurement devices, such as EEG, ECG, and EMG recorders, are available in low-cost, open-source implementations with standard specifications. However, high-end systems remain expensive and predominantly proprietary, limiting accessibility and customization by research laboratories. In addition, neurophysiology techniques such as bioimpedance-based Fast Neural Electrical Impedance Tomography (FN-EIT) also rely on these systems for data acquisition. This work aimed to develop an open-source biopotential recording system using off-the-shelf components that achieves performance comparable to high-end devices.
Approach
We designed our system to provide simultaneous sampling over 32 channels, 24-bit resolution, 10 kHz bandwidth, 50 kHz sampling rate, and battery-powered operation while reducing cost by two orders of magnitude. System performance was evaluated comparatively against a reference device. Initial validation involved benchtop recordings in saline solution and standard non-invasive biopotential measurements (ECG and EMG). Further in-vivo validation was performed by recording evoked electrophysiological responses and FN-EIT traces from the sciatic nerve of a rat during tibial branch stimulation.
Main results
EMG recordings showed comparable RMS peak amplitudes (814±153 µV vs. 897±113µV, p=0.07), while ECG-derived heart rates closely matched between systems (64.8±4.0 bpm vs. 65.1±3.1bpm, p=0.54). During in-vivo recordings, compound action potentials exhibited comparable amplitudes and morphology (129±26 mV vs 128±25 mV, P=0.15). FN-EIT recordings showed strongly correlated baseline voltages (R>0.93, P=0.11), sub-microvolt noise levels (0.83±0.36µV vs. 0.42±0.25µV, p<0.05), and comparable impedance variations (0.006±0.002% vs 0.005±0.003, P>0.05). FN-EIT images of functional activity recorded with the novel device closely matched reference ones, exhibiting a 98.5% overlap in activated area.
Significance
The proposed open-source device has the potential to broaden research access to customizable, high-specification data acquisition hardware and facilitate wider adoption of specialized neural recording techniques such as FN-EIT.
