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