Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI
Joint Authors
Devlaminck, Dieter
Santens, Patrick
Grosse-Wentrup, Moritz
Otte, Georges
Wyns, Bart
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-11
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification.
The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect.
In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase.
Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects.
This paper outlines the details of the multitask CSP algorithm and shows results on two data sets.
In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low.
American Psychological Association (APA)
Devlaminck, Dieter& Wyns, Bart& Grosse-Wentrup, Moritz& Otte, Georges& Santens, Patrick. 2011. Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI. Computational Intelligence and Neuroscience،Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-455455
Modern Language Association (MLA)
Devlaminck, Dieter…[et al.]. Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI. Computational Intelligence and Neuroscience No. 2011 (2011), pp.1-9.
https://search.emarefa.net/detail/BIM-455455
American Medical Association (AMA)
Devlaminck, Dieter& Wyns, Bart& Grosse-Wentrup, Moritz& Otte, Georges& Santens, Patrick. Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI. Computational Intelligence and Neuroscience. 2011. Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-455455
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455455