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The Optimal Number and Distribution of Channels in Mental Fatigue Classification Based on GA-SVM

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Published:27 December 2018Publication History

ABSTRACT

Mental fatigue is closely related to our daily life and work, a considerable number of studies have achieved good results in quantifying and predicting them. Although some studies have achieved a high accuracy by using only a single channel, and a few have explored the optimal solution for feature and channel selection. However, detailed research of optimally setting the electrodes position and determining the number channels are rarely seen. In this study, by designing a novel genetic operator and applying the GA-SVM model, we compared the maximum number of optimal channels and their distributions. The result suggests that the classification accuracy almost reaches its optimum (94.0±5.3 %) when the maximum number of channels reaches 5, and is not affected by the epoch length. The whole brain optimal channels topographic map analysis shows that the optimal channels are mainly distributed in the prefrontal, occipital and temporal lobes, while hardly any is located in the parietal lobe, which indicates that the mental fatigue induced by visual search task characterized similarly among different individuals and highly task-related.

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      • Published in

        cover image ACM Other conferences
        ICBRA '18: Proceedings of the 5th International Conference on Bioinformatics Research and Applications
        December 2018
        111 pages
        ISBN:9781450366113
        DOI:10.1145/3309129

        Copyright © 2018 ACM

        © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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        • Published: 27 December 2018

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