Dataset Open Access
MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks
Wonse Jo;
Ruiqi Wang;
Su Sun;
Revanth Krishna Senthilkumaran;
Daniel Foti;
Byung-Cheol Min
BibTeX Export
@dataset{wonse_jo_2022_7023242,
author = {Wonse Jo and
Ruiqi Wang and
Su Sun and
Revanth Krishna Senthilkumaran and
Daniel Foti and
Byung-Cheol Min},
title = {{MOCAS: A Multimodal Dataset for Objective
Cognitive Workload Assessment on Simultaneous
Tasks}},
month = aug,
year = 2022,
note = {{This material is based upon work supported by the
National Science Foundation under Grant No.
IIS-1846221. Any opinions, findings, and
conclusions or recommendations expressed in this
material are those of the author(s) and do not
necessarily reflect the views of the National
Science Foundation.}},
publisher = {Zenodo},
version = {2022.0.0},
doi = {10.5281/zenodo.7023242},
url = {https://doi.org/10.5281/zenodo.7023242}
}
110
89
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downloads
| All versions | This version | |
|---|---|---|
| Views | 110 | 110 |
| Downloads | 89 | 89 |
| Data volume | 992.9 GB | 992.9 GB |
| Unique views | 86 | 86 |
| Unique downloads | 50 | 50 |
Indexed in
- Publication date:
- August 25, 2022
- DOI:
-
- Keyword(s):
- affective dataset affective computing cognitive load stress rosbag2
- Grants:
-
National Science Foundation:
- CAREER: Adaptive Human Multi-Robot Systems (1846221)
- License (for files):
- Creative Commons Attribution 4.0 International