Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces
Joint Authors
Falk, Tiago H.
Banville, Hubert
Gupta, Rishabh
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-24, 24 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-18
Country of Publication
Egypt
No. of Pages
24
Main Subjects
Abstract EN
Based on recent electroencephalography (EEG) and near-infrared spectroscopy (NIRS) studies that showed that tasks such as motor imagery and mental arithmetic induce specific neural response patterns, we propose a hybrid brain-computer interface (hBCI) paradigm in which EEG and NIRS data are fused to improve binary classification performance.
We recorded simultaneous NIRS-EEG data from nine participants performing seven mental tasks (word generation, mental rotation, subtraction, singing and navigation, and motor and face imagery).
Classifiers were trained for each possible pair of tasks using (1) EEG features alone, (2) NIRS features alone, and (3) EEG and NIRS features combined, to identify the best task pairs and assess the usefulness of a multimodal approach.
The NIRS-EEG approach led to an average increase in peak kappa of 0.03 when using features extracted from one-second windows (equivalent to an increase of 1.5% in classification accuracy for balanced classes).
The increase was much stronger (0.20, corresponding to an 10% accuracy increase) when focusing on time windows of high NIRS performance.
The EEG and NIRS analyses further unveiled relevant brain regions and important feature types.
This work provides a basis for future NIRS-EEG hBCI studies aiming to improve classification performance toward more efficient and flexible BCIs.
American Psychological Association (APA)
Banville, Hubert& Gupta, Rishabh& Falk, Tiago H.. 2017. Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-24.
https://search.emarefa.net/detail/BIM-1140910
Modern Language Association (MLA)
Banville, Hubert…[et al.]. Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-24.
https://search.emarefa.net/detail/BIM-1140910
American Medical Association (AMA)
Banville, Hubert& Gupta, Rishabh& Falk, Tiago H.. Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-24.
https://search.emarefa.net/detail/BIM-1140910
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1140910