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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Understanding Fatigue Through Biosignals: A Comprehensive Dataset

Authors: Gabbi, Marta; Cornia, Luca; Villani, Valeria; Sabattini, Lorenzo;

Understanding Fatigue Through Biosignals: A Comprehensive Dataset

Abstract

Fatigue is a multifaceted construct, that represents an important part of human experience. The two main aspects of fatigue are the mental one and the physical one, that often intertwine, intensifying their collective impact on daily life and overall well-being.To soften this impact, understanding and quantifying fatigue is crucial. Physiological data play a pivotal role in the comprehension of fatigue, allowing a precious insight into the level and type of fatigue experienced. The MePhy dataset includes physiological data gathered while inducing different types of fatigue conditions, in particular mental and physical fatigue. We collected various biosignals closely associated with fatigue (ECG, EDA, EMG and Eye Blinking). Test participants endured a four-part experiment that aimed to elicit mental fatigue, physical fatigue and a combination of both. The main folder contains: MePhy Dataset folder, which contains the dataset; ReadMe.pdf, which provides more informations about the dataset; Mental Fatigue Inducing Test folder, which includes the HTML application used to simulate mental fatigue in the test participants. A more in depth description of the MePhy dataset can be found in the following paper https://doi.org/10.1145/3610977.3637485. Marta Gabbi, Luca Cornia, Valeria Villani, and Lorenzo Sabattini (2024) Understanding Fatigue Through Biosignals: A Comprehensive Dataset. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24).

Keywords

Eye Blinking, EMG, Physical Fatigue, ECG, Fatigue Comprehension, Biosignals, Mental Fatigue, EDA

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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