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Software platform for rapid prototyping of NIRS brain computer interfacing techniques.

Fiachra Matthews¹, Christopher Soraghan, Tomas E Ward

¹Hamilton Institute, National University of Ireland Maynooth, Co. Kildare, Ireland.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 24, 2009

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This study introduces a new control system for optical brain-computer interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS). The system enables real-time testing of signal processing and classification techniques for advanced BCI applications.

Area of Science:

Neuroscience
Biomedical Engineering
Computer Science

Background:

Functional near-infrared spectroscopy (fNIRS) is an emerging modality for brain-computer interfaces (BCIs).
Implementing and testing signal processing and classification techniques for fNIRS-based BCIs requires dedicated systems.
Real-time application testing is crucial for advancing BCI research.

Purpose of the Study:

To describe a novel control system for a next-generation optical brain-computer interface (BCI).
To facilitate the investigation and real-time testing of signal processing and classification techniques within the BCI community.
To provide a configurable platform for hardware control, signal regulation, filtering, and testing.

Main Methods:

Development of a control system using LABVIEW, a graphical programming environment.

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Integration with National Instruments hardware for comprehensive system control.

Implementation of a graphical user interface for easy configuration and real-time testing.

Main Results:

A functional control system for an optical BCI utilizing fNIRS has been successfully developed.
The system allows for complete configurability of hardware and signal processing parameters.
Real-time testing and filtering capabilities are integrated within the graphical interface.

Conclusions:

The described LABVIEW-based system provides a versatile platform for advancing fNIRS-BCI research.
This system supports the development and validation of novel signal processing and classification algorithms.
It enables efficient real-time experimentation crucial for practical BCI applications.