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Updated: Feb 14, 2026

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources
Published on: November 26, 2016
Intsy: a low-cost, open-source, wireless multi-channel bioamplifier system
Jonathan C Erickson1, James A Hayes1, Mauricio Bustamante1
1Department of Physics and Engineering, Washington and Lee University, Lexington, VA 24450, United States of America.
Objective:
Multi-channel electrical recordings of physiologically generated signals are common to a wide range of biomedical fields. The aim of this work was to develop, validate, and demonstrate the practical utility of a high-quality, low-cost 32/64-channel bioamplifier system with real-time wireless data streaming capability.
Approach:
The new 'Intsy' system integrates three main off-the-shelf hardware components: (1) Intan RHD2132 bioamplifier; (2) Teensy 3.2 microcontroller; and (3) RN-42 Bluetooth 2.1 module with a custom LabView interface for real-time data streaming and visualization. Practical utility was validated by measuring serosal gastric slow waves and surface EMG on the forearm with various contraction force levels. Quantitative comparisons were made to a gold-standard commercial system (Biosemi ActiveTwo).
Main Results:
Intsy signal quality was quantitatively comparable to that of the ActiveTwo. Recorded slow wave signals had high SNR (24 ± 2.7 dB) and wavefront propagation was accurately mapped. EMG spike bursts were characterized by high SNR (⩾10 dB) and activation timing was readily identified. Stable data streaming rates achieved were 3.5 kS s-1 for wireless and 64 kS s-1 for USB-wired transmission.
Significance:
Intsy has the highest channel count of any existing open-source, wireless-enabled module. The flexibility, portability and low cost ($1300 for the 32-channel version, or $2500 for 64 channels) of this new hardware module reduce the entry barrier for a range of electrophysiological experiments, as are typical in the gastrointestinal (EGG), cardiac (ECG), neural (EEG), and neuromuscular (EMG) domains.
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