Coyle, Shirley M, Ward, Tomás E and Markham, Charles M (2007) Brain–computer interface using a simplified functional near-infrared spectroscopy system. Journal of Neural Engineering, 4 (3). pp. 219-226. ISSN 1741-2560
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Abstract
A brain–computer interface (BCI) is a device that allows a user to communicate with external
devices through thought processes alone. A novel signal acquisition tool for BCIs is
near-infrared spectroscopy (NIRS), an optical technique to measure localized cortical brain
activity. The benefits of using this non-invasive modality are safety, portability and
accessibility. A number of commercial multi-channel NIRS system are available; however we
have developed a straightforward custom-built system to investigate the functionality of a
fNIRS-BCI system. This work describes the construction of the device, the principles of
operation and the implementation of a fNIRS-BCI application, ‘Mindswitch’ that harnesses
motor imagery for control. Analysis is performed online and feedback of performance is
presented to the user. Mindswitch presents a basic ‘on/off’ switching option to the user, where
selection of either state takes 1 min. Initial results show that fNIRS can support simple BCI
functionality and shows much potential. Although performance may be currently inferior to
many EEG systems, there is much scope for development particularly with more sophisticated
signal processing and classification techniques. We hope that by presenting fNIRS as an
accessible and affordable option, a new avenue of exploration will open within the BCI
research community and stimulate further research in fNIRS-BCIs.
Item Type: | Article |
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Keywords: | Brain–computer; interface; simplified functional; near-infrared; spectroscopy system; |
Academic Unit: | Assisting Living & Learning,ALL institute Faculty of Science and Engineering > Chemistry Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 15548 |
Identification Number: | 10.1088/1741-2560/4/3/007 |
Depositing User: | Dr. Charles Markham |
Date Deposited: | 22 Feb 2022 12:09 |
Journal or Publication Title: | Journal of Neural Engineering |
Publisher: | IOP Publishing |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/15548 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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