EEG-based mental workload recognition using deep learning techniques
In most cases, mental workload (MWL) refers to the cost of cognitive resources in a certain task. [1]. A high MWL means the subject uses most of cognitive resources on the given task. Understanding the MWL level induced is important for optimizing human resources and reducing accidents. But in most...
Saved in:
Main Author: | Zeng, Chenxuan |
---|---|
Other Authors: | Wang Lipo |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/140005 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
EEG mental workload recognition using deep learning techniques
by: Tay, Nicholas Zhi Peng
Published: (2019) -
EEG-based mental workload recognition using deep learning techniques
by: Koh, Charis Hwee Ying
Published: (2018) -
EEG-based cognitive workload recognition using deep learning techniques
by: Zhang, Chunlin
Published: (2021) -
EEG-based emotion recognition using deep learning techniques
by: Lang, Zihui
Published: (2020) -
EEG-based emotion recognition using deep learning techniques
by: Song, Wenyi
Published: (2021)