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...
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Published in | Frontiers in neuroscience Vol. 14; p. 549524 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Research Foundation
01.12.2020
Frontiers Media S.A |
Subjects | |
Online Access | Get full text |
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Summary: | 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/
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience Edited by: Ana Matran-Fernandez, University of Essex, United Kingdom Reviewed by: Christoph Tremmel, University of Essex, United Kingdom; Pietro Aricò, Sapienza University of Rome, Italy |
ISSN: | 1662-453X 1662-4548 1662-453X |
DOI: | 10.3389/fnins.2020.549524 |