Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-22095-1_62
Title: EEG-based measure of cognitive workload during a mental arithmetic task
Authors: Rebsamen, B. 
Kwok, K. 
Penney, T.B.
Keywords: arithmetic
cognitive state
EEG
mental workload
Issue Date: 2011
Citation: Rebsamen, B.,Kwok, K.,Penney, T.B. (2011). EEG-based measure of cognitive workload during a mental arithmetic task. Communications in Computer and Information Science 174 CCIS (PART 2) : 304-307. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-22095-1_62
Abstract: We collected EEG data from 16 subjects while they performed a mental arithmetic task at five different levels of difficulty. A classifier was trained to discriminate between three conditions: relaxed, low workload and high workload, using spectral features of the EEG. We obtained an average classification accuracy of 62%. A continuous workload index was obtained by low-pass filtering the classifier's output. The average correlation coefficient between the resulting workload index and the difficulty level of the task was 0.6. © 2011 Springer-Verlag.
Source Title: Communications in Computer and Information Science
URI: http://scholarbank.nus.edu.sg/handle/10635/115406
ISBN: 9783642220944
ISSN: 18650929
DOI: 10.1007/978-3-642-22095-1_62
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