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Collecting Data for Machine Learning on Office Workers’ Attention, Fatigue, Overload, and Stress during Computer Use

Topics: Assistive AI tools for task optimization at individual and team level (e.g. team formation, resources optimization) ; Computational intelligence applications in working environments ; Decision support systems and personalized interventions for workability sustainability ; ICT tools for modelling and monitoring worker state (functional abilities, cognitive capacity, mental fatigue, workload, etc.), activity, behaviour and emotional status ; Virtual worker and workplace models and simulation tools ; Worker-centric systems and solutions

Author: Rita Kovordanyi

Affiliation: Department og Computer and Information Science, Linköping University, Sweden

Keyword(s): Cognitive State Prediction, Machine Learning, Office Work.

Abstract: Predicting a computer user’s covert cognitive state, such as attention, has previously proven to be difficult, as cognitive states are induced trough complex interaction of hidden brain processes that are difficult to capture in a traditional rule-based methods. An alternative approach to modeling cognitive states is through machine learning, which however, requires that a wide range of data is collected from the user. In this paper, we describe our software for collecting a wide range of data from office workers’ during everyday computer work. The data collection process is relatively unobtrusive, as it can be run as a background process on the user’s computer and does not require extensive computational resources. We conclude by discussing practical issues, such as data sample frequency, where one wants to strike a balance between good enough data quality for machine learning and unobtrusiveness for the user.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kovordanyi, R. (2021). Collecting Data for Machine Learning on Office Workers’ Attention, Fatigue, Overload, and Stress during Computer Use. In Proceedings of the 13th International Joint Conference on Computational Intelligence - SmartWork; ISBN 978-989-758-534-0; ISSN 2184-3236, SciTePress, pages 468-476. DOI: 10.5220/0010727800003063

@conference{smartwork21,
author={Rita Kovordanyi.},
title={Collecting Data for Machine Learning on Office Workers’ Attention, Fatigue, Overload, and Stress during Computer Use},
booktitle={Proceedings of the 13th International Joint Conference on Computational Intelligence - SmartWork},
year={2021},
pages={468-476},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010727800003063},
isbn={978-989-758-534-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence - SmartWork
TI - Collecting Data for Machine Learning on Office Workers’ Attention, Fatigue, Overload, and Stress during Computer Use
SN - 978-989-758-534-0
IS - 2184-3236
AU - Kovordanyi, R.
PY - 2021
SP - 468
EP - 476
DO - 10.5220/0010727800003063
PB - SciTePress

- Science and Technology Publications, Lda.
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