Development of double density whole brain fNIRS with EEG system for brain machine interface

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Non-invasive Brain-Machine Interfaces (BMI) offer significant potential for improving quality of life, particularly for individuals with disabilities.
• Current non-invasive BMI systems, often utilizing electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS), face challenges in accuracy and measurement area restriction for clinical translation.
• Advancing BMI technology is crucial for restoring lost function, rehabilitation, and enabling direct brain control of external devices.

Purpose of the Study:

• To develop a high-accuracy brain activity measurement system by integrating fNIRS and EEG.
• To enhance the performance of non-invasive BMI for broader clinical and daily-life applications.
• To address the key factors of high-accuracy signal decoding and restricted measurement areas for clinical adoption of BMI.

Main Methods:

• Development of a novel, high-performance fNIRS system.
• Implementation of a double density technique to achieve high spatial resolution in fNIRS.
• Integration of a large number of measurement channels to cover the entire human brain.

Main Results:

• The developed fNIRS system demonstrated high performance and high spatial resolution.
• The combined fNIRS and EEG system enables high-accuracy brain activity measurement.
• The system's design facilitates restricted measurement areas, a key factor for clinical translation.

Conclusions:

• The integrated fNIRS and EEG system represents a significant advancement in non-invasive brain-machine interfaces.
• This technology has the potential to move non-invasive BMI from laboratory settings to clinical applications.
• The enhanced brain activity measurement capabilities can broaden the applicability of BMI for rehabilitation and daily device control.