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A common spatial pattern approach for classification of mental counting and motor execution EEG
Name
mental_counting_ihci.pdf
Description
Accepted version
Size
2.5 MB
Format
Adobe PDF
Checksum (MD5)
98f19f31173e0a89400ef685088cdedc
Author(s)
Goel, Purvi
Joshi, Raviraj
Sur, Mriganka
Murthy, Hema A.
Date Issued
December 2018
Publisher
Springer International Publishing
Citation
Goel, Purvi, Joshi, Raviraj, Sur, Mriganka and Murthy, Hema A. 2018. "A common spatial pattern approach for classification of mental counting and motor execution EEG."
Version
Author's final manuscript
Abstract
© Springer Nature Switzerland AG 2018. A Brain Computer Interface (BCI) as a medium of communication is convenient for people with severe motor disabilities. Although there are a number of different BCIs, the focus of this paper is on Electroencephalography (EEG) as a means of human computer interaction. Motor imagery and mental arithmetic are the most popular techniques used to modulate brain waves that can be used to control devices. We show that it is possible to define different mental states using real fist rotation and imagined reverse counting. While people have already investigated left fist rotation and right fist rotation for dual state BCI, we intend to define a new state using mental reverse counting. We use Common Spatial Pattern (CSP) approach for feature extraction to distinguish between these states. CSP has been prominently used in the context of motor imagery task, we define its applicability for the distinction between motor execution and mental counting. CSP features are evaluated using classifiers like GMM, SVM, and GMM-UBM. GMM-UBM using data filtered through the beta band (13–30 Hz) gives the best performance.
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1007/978-3-030-04021-5_3
