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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 11
3371-3375

Novel multiclass classification framework with multi-branch LSTM and attention mechanism for mental workload evaluation

Feng Yuana,b,c,d
Li Yanleia,b,c,d
Li Yifana,b,c,d
Zhang Boa
Ding Jinhonge
Xia Likuna,b,c,d
a. College of Information Engineering, b. Laboratory of Neural Computing & Intelligent Perception(NCIP), c. International Science & Technology Cooperation Base of Electronic System Reliability & Mathematical Interdisciplinary, d. Beijing Advanced Innovation Center for Imaging Theory & Technology, e. Dept. of Psychology, Capital Normal University, Beijing 100048, China
DOI: 10.19734/j.issn.1001-3695.2021.04.0142

Abstract

It is critical to obtain sufficient and effective EEG features in mental workload evaluation. This paper presented a multiclass classification network which combined multi-branch LSTM with attention mechanism. Firstly, this network segmented an EEG signal into a number of temporal slices, in each of which multi-branch LSTM extracted temporal feature from the EEG slices. Then attention mechanism optimized the features. Finally, softmax function evaluated mental workload level. The experimental results show that the performance of the proposed network is better than that of the existing network in both binary class and multiclass classification task.

Foundation Support

北京自然科学基金面上项目(BNSF)(4202011)
中国自然科学基金面上项目(NSFC)(61572076)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0142
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: System Development & Application
Pages: 3371-3375
Serial Number: 1001-3695(2021)11-029-3371-05

Publish History

[2021-11-05] Printed Article

Cite This Article

冯源, 李彦蕾, 李一凡, 等. 基于注意力机制的多分支LSTM心理负荷评估模型 [J]. 计算机应用研究, 2021, 38 (11): 3371-3375. (Feng Yuan, Li Yanlei, Li Yifan, et al. Novel multiclass classification framework with multi-branch LSTM and attention mechanism for mental workload evaluation [J]. Application Research of Computers, 2021, 38 (11): 3371-3375. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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