New methods for stress assessment and monitoring at the workplace
Article
Carneiro, D., Novais, P., Augusto, J. and Payne, N. 2019. New methods for stress assessment and monitoring at the workplace. IEEE Transactions on Affective Computing. 10 (2), pp. 237-254. https://doi.org/10.1109/TAFFC.2017.2699633
Type | Article |
---|---|
Title | New methods for stress assessment and monitoring at the workplace |
Authors | Carneiro, D., Novais, P., Augusto, J. and Payne, N. |
Abstract | The topic of stress is nowadays a very important one, not only in research but on social life in general. People are increasingly aware of this problem and its consequences at several levels: health, social life, work, quality of life, etc. This resulted in a significant increase in the search for devices and applications to measure and manage stress in real-time. Recent technological and scientific evolution fosters this interest with the development of new methods and approaches. In this paper we survey these new methods for stress assessment, focusing especially on those that are suited for the workplace: one of today’s major sources of stress. We contrast them with more traditional methods and compare them between themselves, evaluating nine characteristics. Given the diversity of methods that exist nowadays, this work facilitates the stakeholders’ decision towards which one to use, based on how much their organization values aspects such as privacy, accuracy, cost-effectiveness or intrusiveness |
Keywords | Stress, Human-Computer Interaction, Survey, Ambient Intelligence |
Research Group | Research Group on Development of Intelligent Environments |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Journal | IEEE Transactions on Affective Computing |
ISSN | 1949-3045 |
Publication dates | |
Online | 27 Apr 2017 |
06 Jun 2019 | |
Publication process dates | |
Deposited | 11 May 2017 |
Accepted | 25 Apr 2017 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TAFFC.2017.2699633 |
Language | English |
https://repository.mdx.ac.uk/item/86z16
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