Application to robot control using brain function measurement by near-infrared spectroscopy.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Brain-computer interfaces (BCIs) are increasingly researched, with electroencephalography (EEG) being a common method.
• Near-infrared spectroscopy (NIRS) presents a viable alternative due to its portable and noninvasive measurement capabilities.
• NIRS is recognized for its potential in developing versatile and accessible BCIs.

Purpose of the Study:

• To explore the application of NIRS for ON/OFF control in brain-computer interfaces.
• To develop a quantitative method for estimating movement timing using NIRS data.
• To assess the feasibility of NIRS in real-time BCI control applications.

Main Methods:

• Regional cerebral blood flow was measured using NIRS during voluntary tapping movements of the right hand.
• A neural network was employed to analyze NIRS data and estimate movement onset and offset.
• Data processing focused on identifying distinct patterns in cerebral blood flow associated with motor activity.

Main Results:

• The study successfully demonstrated the potential of NIRS for BCI control.
• A method was proposed and validated for quantitatively estimating the start and end timings of hand movements.
• NIRS signals showed reliable correlations with the execution of the tapping task.

Conclusions:

• NIRS is a promising technology for developing practical and noninvasive brain-computer interfaces.
• The proposed neural network-based method enables accurate estimation of movement timing from NIRS data.
• NIRS-based BCIs hold potential for applications requiring simple ON/OFF control, such as motor rehabilitation or assistive technologies.