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    Brain–computer interface using a simplified functional near-infrared spectroscopy system


    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
    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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