Abstract
In the last years the impact of stress on the society has been increased, resulting in 77% of people that regularly experiences physical symptoms caused by stress with a negative impact on their personal and professional life, especially in aging working population. This paper aims to demonstrate the feasibility of detection and monitoring of stress, inducted by mental stress tests, through the analysis of physiological data collected by wearable sensors. In fact, the physiological features extracted from heart rate variability and galvanic skin response showed significant differences between stressed and not stressed people. Starting from the physiological data, the work provides also a cluster analysis based on Principal Components (PCs) able to showed a visual discrimination of stressed and relaxed groups. The developed system would support active ageing, monitoring and managing the level of stress in ageing workers and allowing them to reduce the burden of stress related to the workload on the basis of personalized interventions.
Giorgia Acerbi, Erika Rovini, Stefano Betti Equal contribution to the work.
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Acknowledgments
This work was supported by research funding provided by Trans.Safe (AmbienT Response to Avoid Negative Stress and enhance SAFEty, www.transsafe.eu) project—6th call of the Ambient Assisted Living Joint Programme (AAL JP) with the topic “ICT-based Solutions for Supporting Occupation in Life of Older Adults”
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Acerbi, G. et al. (2017). A Wearable System for Stress Detection Through Physiological Data Analysis. In: Cavallo, F., Marletta, V., Monteriù, A., Siciliano, P. (eds) Ambient Assisted Living. ForItAAL 2016. Lecture Notes in Electrical Engineering, vol 426. Springer, Cham. https://doi.org/10.1007/978-3-319-54283-6_3
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DOI: https://doi.org/10.1007/978-3-319-54283-6_3
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