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WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity
Assessment of mental workload is crucial for applications that require sustained attention and where conditions such as mental fatigue and drowsiness must be avoided. Previous work that attempted to devise objective methods to model mental workload were mainly based on neurological or physiological...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736238/ https://www.ncbi.nlm.nih.gov/pubmed/33335465 http://dx.doi.org/10.3389/fnins.2020.549524 |
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author | Albuquerque, Isabela Tiwari, Abhishek Parent, Mark Cassani, Raymundo Gagnon, Jean-François Lafond, Daniel Tremblay, Sébastien Falk, Tiago H. |
author_facet | Albuquerque, Isabela Tiwari, Abhishek Parent, Mark Cassani, Raymundo Gagnon, Jean-François Lafond, Daniel Tremblay, Sébastien Falk, Tiago H. |
author_sort | Albuquerque, Isabela |
collection | PubMed |
description | Assessment of mental workload is crucial for applications that require sustained attention and where conditions such as mental fatigue and drowsiness must be avoided. Previous work that attempted to devise objective methods to model mental workload were mainly based on neurological or physiological data collected when the participants performed tasks that did not involve physical activity. While such models may be useful for scenarios that involve static operators, they may not apply in real-world situations where operators are performing tasks under varying levels of physical activity, such as those faced by first responders, firefighters, and police officers. Here, we describe WAUC, a multimodal database of mental Workload Assessment Under physical aCtivity. The study involved 48 participants who performed the NASA Revised Multi-Attribute Task Battery II under three different activity level conditions. Physical activity was manipulated by changing the speed of a stationary bike or a treadmill. During data collection, six neural and physiological modalities were recorded, namely: electroencephalography, electrocardiography, breathing rate, skin temperature, galvanic skin response, and blood volume pulse, in addition to 3-axis accelerometry. Moreover, participants were asked to answer the NASA Task Load Index questionnaire after each experimental section, as well as rate their physical fatigue level on the Borg fatigue scale. In order to bring our experimental setup closer to real-world situations, all signals were monitored using wearable, off-the-shelf devices. In this paper, we describe the adopted experimental protocol, as well as validate the subjective, neural, and physiological data collected. The WAUC database, including the raw data and features, subjective ratings, and scripts to reproduce the experiments reported herein will be made available at: http://musaelab.ca/resources/. |
format | Online Article Text |
id | pubmed-7736238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77362382020-12-16 WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity Albuquerque, Isabela Tiwari, Abhishek Parent, Mark Cassani, Raymundo Gagnon, Jean-François Lafond, Daniel Tremblay, Sébastien Falk, Tiago H. Front Neurosci Neuroscience Assessment of mental workload is crucial for applications that require sustained attention and where conditions such as mental fatigue and drowsiness must be avoided. Previous work that attempted to devise objective methods to model mental workload were mainly based on neurological or physiological data collected when the participants performed tasks that did not involve physical activity. While such models may be useful for scenarios that involve static operators, they may not apply in real-world situations where operators are performing tasks under varying levels of physical activity, such as those faced by first responders, firefighters, and police officers. Here, we describe WAUC, a multimodal database of mental Workload Assessment Under physical aCtivity. The study involved 48 participants who performed the NASA Revised Multi-Attribute Task Battery II under three different activity level conditions. Physical activity was manipulated by changing the speed of a stationary bike or a treadmill. During data collection, six neural and physiological modalities were recorded, namely: electroencephalography, electrocardiography, breathing rate, skin temperature, galvanic skin response, and blood volume pulse, in addition to 3-axis accelerometry. Moreover, participants were asked to answer the NASA Task Load Index questionnaire after each experimental section, as well as rate their physical fatigue level on the Borg fatigue scale. In order to bring our experimental setup closer to real-world situations, all signals were monitored using wearable, off-the-shelf devices. In this paper, we describe the adopted experimental protocol, as well as validate the subjective, neural, and physiological data collected. The WAUC database, including the raw data and features, subjective ratings, and scripts to reproduce the experiments reported herein will be made available at: http://musaelab.ca/resources/. Frontiers Media S.A. 2020-12-01 /pmc/articles/PMC7736238/ /pubmed/33335465 http://dx.doi.org/10.3389/fnins.2020.549524 Text en Copyright © 2020 Albuquerque, Tiwari, Parent, Cassani, Gagnon, Lafond, Tremblay and Falk. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Albuquerque, Isabela Tiwari, Abhishek Parent, Mark Cassani, Raymundo Gagnon, Jean-François Lafond, Daniel Tremblay, Sébastien Falk, Tiago H. WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title | WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title_full | WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title_fullStr | WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title_full_unstemmed | WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title_short | WAUC: A Multi-Modal Database for Mental Workload Assessment Under Physical Activity |
title_sort | wauc: a multi-modal database for mental workload assessment under physical activity |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736238/ https://www.ncbi.nlm.nih.gov/pubmed/33335465 http://dx.doi.org/10.3389/fnins.2020.549524 |
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