EEG fatigue detection method based on attention mechanism and multifeature fusion convolutional neural network

Duanyuan Bai; Tingyi Wu; Yingjie Shi; Yongheng Zhang; Qiyue Yuan; Ruizhe Li

doi:10.1117/12.3055400

12 December 2024 EEG fatigue detection method based on attention mechanism and multifeature fusion convolutional neural network

Duanyuan Bai, Tingyi Wu, Yingjie Shi, Yongheng Zhang, Qiyue Yuan, Ruizhe Li

Author Affiliations +

Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134391Z (2024) https://doi.org/10.1117/12.3055400
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China

Abstract

To address the complexities and incompleteness of manual electroencephalogram (EEG) feature extraction, this paper proposes a fatigue detection method based on a multi-feature fusion convolutional neural network with an attention mechanism. This approach aims to achieve more accurate and comprehensive fatigue detection and analysis. The EEG data from the SEED-VIG dataset is denoised and segmented, with 4D features extracted and generated. These features are then input into spatial, frequency, and temporal attention modules for fusion, resulting in the output of final fatigue detection results. Testing on SEED-VIG samples demonstrates that the proposed algorithm achieves a correct recognition rate of 82.21%, thus validating its effectiveness.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Duanyuan Bai, Tingyi Wu, Yingjie Shi, Yongheng Zhang, Qiyue Yuan, and Ruizhe Li "EEG fatigue detection method based on attention mechanism and multifeature fusion convolutional neural network", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134391Z (12 December 2024); https://doi.org/10.1117/12.3055400

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Electroencephalography

Material fatigue

Denoising

Signal detection

Signal processing

Convolutional neural networks

Brain

Show All Keywords

Keywords/Phrases

Search In:

Publication Years