Assessing Operator Wellbeing through Physiological Measurements in Real-Time—Towards Industrial Application †
Department of Industrial and Materials Science, Chalmers University of Technology, Hörsalsvägen 7A, SE-41296 Gothenburg, Sweden
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Author to whom correspondence should be addressed.
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This paper is an extended version of our paper published in Advances in Neuroergonomics and Cognitive Engineering, Springer, Switzerland , Cham, 2017; pp. 223–232.
Technologies 2017, 5(4), 61; https://doi.org/10.3390/technologies5040061
Received: 2 July 2017
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Revised: 13 September 2017
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Accepted: 20 September 2017
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Published: 22 September 2017
(This article belongs to the Special Issue Personal Health and Wellbeing Intelligent Systems Based on Wearable and Mobile Technologies)
This article focuses on how operator wellbeing can be assessed to ensure social sustainability and operator performance at assembly stations. Rapid technological advances provide possibilities for assessing wellbeing in real-time, and from an assembly system perspective, this could enable the assessment of physiological data in real-time. While technology is available, it has not been implemented or tested in industry. The aim of this paper was to investigate empirically how concurrent physiological measurement technologies can be integrated into an industrial application, in order to increase operator wellbeing and operator performance. A mixed method approach was used, which included a literature study, two laboratory tests, two case studies and a workshop. The results indicated that operator wellbeing could be assessed through electro-dermal activity, but that the data is perceived as difficult to interpret. For an industrial application, operator perception and data presentation are important and risks connected to personal integrity and IT-support need to be addressed. Future work includes testing how a combination of physiological measures and self-assessments can be used to assess operator wellbeing in an industrial context.
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Externally hosted supplementary file 1
Doi: 10.1007/978-3-319-41691-5_19, https://doi.org/10.1016/j.procir.2016.05.013, https://doi.org/10.1016/j.procir.2016.02.158
Description: This paper is based on previous research on evaluation of smart devices, http://www.sciencedirect.com/science/article/pii/S2212827116304589, on how to assess operator emotion objectively, https://link.springer.com/chapter/10.1007/978-3-319-41691-5_19 and on the relationship between operator emotion and performance, http://www.sciencedirect.com/science/article/pii/S221282711600442X.
MDPI and ACS Style
Mattsson, S.; Fast-Berglund, Å.; Åkerman, M. Assessing Operator Wellbeing through Physiological Measurements in Real-Time—Towards Industrial Application. Technologies 2017, 5, 61. https://doi.org/10.3390/technologies5040061
AMA Style
Mattsson S, Fast-Berglund Å, Åkerman M. Assessing Operator Wellbeing through Physiological Measurements in Real-Time—Towards Industrial Application. Technologies. 2017; 5(4):61. https://doi.org/10.3390/technologies5040061
Chicago/Turabian StyleMattsson, Sandra, Åsa Fast-Berglund, and Magnus Åkerman. 2017. "Assessing Operator Wellbeing through Physiological Measurements in Real-Time—Towards Industrial Application" Technologies 5, no. 4: 61. https://doi.org/10.3390/technologies5040061
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