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Man-Machine-Environment System Engineering and Its Historical Mission Read chapter Read first chapter

2022 | OriginalPaper | Chapter

Study on EEG Channel Selection for Visual Manipulation Tasks

Authors : Hongquan Qu, Min Liu, Liping Pang, Hongbin Qu, Ling Wang

Published in: Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE

Publisher: Springer Singapore

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Abstract

At present, electroencephalogram (EEG) has been widely used in the classification of mental workload. But most of the EEG acquisition devices used in the research a use a large number of electrodes. However, this brings high hardware costs, limited portability and discomfort to the wearer. In addition, most of the channels have information redundancy and noise interference, which have a negative impact on the subsequent mental workload classification. Therefore, it is necessary to use fewer channels to accurately identify the mental load of the operator. Focusing on the above problems, a method of channel selection based on Davies–Bouldin Index (DBI) for visual manipulation tasks is proposed in this paper, it selects effective channels by analyzing the differences between the features of low and high workload data.

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Metadata
Title
Study on EEG Channel Selection for Visual Manipulation Tasks
Authors
Hongquan Qu
Min Liu
Liping Pang
Hongbin Qu
Ling Wang
Copyright Year
2022
Publisher
Springer Singapore
Book
Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE

Print ISBN: 978-981-16-5962-1

Electronic ISBN: 978-981-16-5963-8

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-5963-8_40

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