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

Biology

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