Toward Mobile Neuroimaging: Design of a Multi-Modal EEG/fNIRS Instrument for Real-Time Use.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Wearable Technology

Background:

• Traditional neurophysiological monitoring systems are often tethered, limiting ambulatory research.
• Integrating electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) offers complementary insights into brain activity.
• The need for portable, high-fidelity, and wireless solutions is critical for advancing mobile brain imaging.

Purpose of the Study:

• To design and develop a mobile, multi-modal EEG/fNIRS device for wireless neurophysiological monitoring.
• To achieve high signal fidelity, low power consumption, and fully untethered operation for ambulatory research.
• To create a scalable and cost-effective platform for synchronized EEG/fNIRS acquisition.

Main Methods:

• Engineered a system integrating ADS1299 biopotential amplifiers (up to 32 channels) and optical front-end components (LEDs, photodiodes).
• Utilized STM32H7 microcontroller for signal control/processing and ESP32-S2 for Wi-Fi communication, employing galvanic isolation and multi-rail power management.
• Implemented a clock-driven acquisition loop and RTOS for data streaming via Wi-Fi using the Lab Streaming Layer (LSL) framework.

Main Results:

• Successfully demonstrated 32-channel synchronized EEG acquisition and fNIRS breath-hold response.
• Validated real-time ECG and optical pulse streaming via LSL.
• The device achieved high signal fidelity, low power consumption, and untethered operation suitable for mobile neuroimaging.

Conclusions:

• The developed mobile EEG/fNIRS device provides a compact, integrated platform for synchronized neurophysiological data acquisition.
• The system enables scalable, low-cost ambulatory brain research with wireless, high-fidelity monitoring.
• Future potential includes embedded edge-machine-learning for on-device signal processing and artifact rejection.