A Rapid Detection Platform for Mental Workload

DOI

10.2991/978-2-38476-346-7_17How to use a DOI?

Keywords

mental workload detection; speech voiceprint information; machine learning algorithm

Abstract

In order to ensure safe production and solve the problem of time-consuming and labor-intensive for human mental workload detection, we have developed a fast detection platform for human mental workload. This platform can quickly detect the mental load of subjects by analyzing their voice data, physiological data, biochemical data and psychological data. The experimental results indicate that the platform could rapidly detect the mental workload, with an accuracy rate of over 75%.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiujie Gao
AU  - Kefeng Ma
AU  - Kun Wang
AU  - Bo Fu
AU  - Yingwen Zhu
AU  - Xiaojun She
AU  - Honglian Yang
AU  - Bo Cui
PY  - 2024
DA  - 2024/12/27
TI  - A Rapid Detection Platform for Mental Workload
BT  - Proceeding of the 2024 International Conference on Diversified Education and Social Development (DESD 2024)
PB  - Atlantis Press
SP  - 124
EP  - 132
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-346-7_17
DO  - 10.2991/978-2-38476-346-7_17
ID  - Gao2024
ER  -