STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA

Liping Pang; Xiyue Wang; Jie Zhang; Xiaoru Wanyan; Xin Wang; Jin Liang; Liang Zhang

doi:10.1049/icp.2021.0445

STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA

Liping Pang^*
, Xiyue Wang
, Jie Zhang
, Xiaoru Wanyan
, Xin Wang
, Jin Liang
, Liang Zhang

^*Corresponding author for this work

School of Aeronautic Science and Engineering

Shenyang Aerospace University
Beihang University
China Institute of Marine Technology & Economy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In a modern human-machine system, it is very meaningful to study the subject-specific mental workload classification for the increasing high mental workload. In this paper, EEG data is used to build the Subject-specific Classifiers (SSCs) based on Stochastic Configuration Network (SCN). SCN has the advantage of random neural network, and can realize the hyper-parameters setting. The results show that the SSCs built in this paper perform well, the range of SSCs test accuracies is between 56.5% and 90.2% with an average of 75.9%.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	683-687
Number of pages	5
Volume	2020
Edition	3
ISBN (Electronic)	9781839534195
DOIs	https://doi.org/10.1049/icp.2021.0445
State	Published - 2020
Event	2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020 - Virtual, Online Duration: 18 Sep 2020 → 21 Sep 2020

Conference

Conference	2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020
City	Virtual, Online
Period	18/09/20 → 21/09/20

Keywords

MENTAL WORKLOAD
STOCHASTIC CONFIGURATION NETWORK
SUBJECT-SPECIFIC CLASSIFIER

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10.1049/icp.2021.0445

Cite this

@inproceedings{b37c4de9f17946a798c576794597901c,

title = "STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA",

abstract = "In a modern human-machine system, it is very meaningful to study the subject-specific mental workload classification for the increasing high mental workload. In this paper, EEG data is used to build the Subject-specific Classifiers (SSCs) based on Stochastic Configuration Network (SCN). SCN has the advantage of random neural network, and can realize the hyper-parameters setting. The results show that the SSCs built in this paper perform well, the range of SSCs test accuracies is between 56.5\% and 90.2\% with an average of 75.9\%.",

keywords = "MENTAL WORKLOAD, STOCHASTIC CONFIGURATION NETWORK, SUBJECT-SPECIFIC CLASSIFIER",

author = "Liping Pang and Xiyue Wang and Jie Zhang and Xiaoru Wanyan and Xin Wang and Jin Liang and Liang Zhang",

note = "Publisher Copyright: {\textcopyright} 2020 The Institution of Engineering and Technology.; 2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020 ; Conference date: 18-09-2020 Through 21-09-2020",

year = "2020",

doi = "10.1049/icp.2021.0445",

language = "英语",

volume = "2020",

pages = "683--687",

booktitle = "IET Conference Proceedings",

publisher = "Institution of Engineering and Technology",

address = "英国",

edition = "3",

}

Pang, L, Wang, X, Zhang, J, Wanyan, X, Wang, X, Liang, J & Zhang, L 2020, STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA. in IET Conference Proceedings. 3 edn, vol. 2020, Institution of Engineering and Technology, pp. 683-687, 2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020, Virtual, Online, 18/09/20. https://doi.org/10.1049/icp.2021.0445

TY - GEN

T1 - STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA

AU - Pang, Liping

AU - Wang, Xiyue

AU - Zhang, Jie

AU - Wanyan, Xiaoru

AU - Wang, Xin

AU - Liang, Jin

AU - Zhang, Liang

PY - 2020

Y1 - 2020

N2 - In a modern human-machine system, it is very meaningful to study the subject-specific mental workload classification for the increasing high mental workload. In this paper, EEG data is used to build the Subject-specific Classifiers (SSCs) based on Stochastic Configuration Network (SCN). SCN has the advantage of random neural network, and can realize the hyper-parameters setting. The results show that the SSCs built in this paper perform well, the range of SSCs test accuracies is between 56.5% and 90.2% with an average of 75.9%.

AB - In a modern human-machine system, it is very meaningful to study the subject-specific mental workload classification for the increasing high mental workload. In this paper, EEG data is used to build the Subject-specific Classifiers (SSCs) based on Stochastic Configuration Network (SCN). SCN has the advantage of random neural network, and can realize the hyper-parameters setting. The results show that the SSCs built in this paper perform well, the range of SSCs test accuracies is between 56.5% and 90.2% with an average of 75.9%.

KW - MENTAL WORKLOAD

KW - STOCHASTIC CONFIGURATION NETWORK

KW - SUBJECT-SPECIFIC CLASSIFIER

UR - https://www.scopus.com/pages/publications/85174649741

U2 - 10.1049/icp.2021.0445

DO - 10.1049/icp.2021.0445

M3 - 会议稿件

AN - SCOPUS:85174649741

VL - 2020

SP - 683

EP - 687

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020

Y2 - 18 September 2020 through 21 September 2020

ER -

STUDY ON BUILDING SUBJECT-SPECIFIC CLASSIFIERS BASED ON EEG DATA

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Keywords

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