Open-source, high-speed and high-resolution data acquisition platform for biopotential recordings and neural EIT applications

Achoimre

Abstract Objective. Biopotential measurement devices, such as electroencephalography, electrocardiography (ECG), and electromyography (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 µ V vs 897 ± 113 µ V, p = 0.07), while ECG-derived heart rates closely matched between systems (64.8 ± 4.0 bpm vs 65.1 ± 3.1 bpm, 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 ± 0.36 µ V vs 0.42 ± 0.25 µ V, 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.