Detecting attention level as a warning sign for online classes by using EEG signals

Yihang Duanmu; Shilong Wang; Jiarun Ding; Xuanming Jin

doi:10.1117/12.2626679

20 December 2021 Detecting attention level as a warning sign for online classes by using EEG signals

Yihang Duanmu, Shilong Wang, Jiarun Ding, Xuanming Jin

Author Affiliations +

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 1215511 (2021) https://doi.org/10.1117/12.2626679
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

When Online learning got popular during the COVID-19 pandemic, tracking students’ in-class attention became a troublesome business. Our experiment is designed to find the possibility and reliability of using EEG signals to detect students’ attention level and ultimately determine whether detecting EEG signals can help online classes. It turns out human’s attention level could be determined, and such property could be used to develop certain device to help online teaching.

Citation Download Citation

Yihang Duanmu, Shilong Wang, Jiarun Ding, and Xuanming Jin "Detecting attention level as a warning sign for online classes by using EEG signals", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 1215511 (20 December 2021); https://doi.org/10.1117/12.2626679

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