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.

A wearable system for stress detection through physiological data analysis / ACERBI, GIORGIA; ROVINI, Erika; BETTI, STEFANO; Tirri, Antonio; Rã³nai, Judit Flóra; Sirianni, Antonella; Agrimi, Jacopo; Eusebi, Lorenzo; CAVALLO, Filippo. - ELETTRONICO. - 426:(2017), pp. 31-50. (Intervento presentato al convegno 7th Italian Forum on Ambient Assisted Living, ForitAAL 2016 tenutosi a ita nel 2016) [10.1007/978-3-319-54283-6_3].

A wearable system for stress detection through physiological data analysis

ROVINI, Erika;CAVALLO, Filippo
2017

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.
2017
Lecture Notes in Electrical Engineering
7th Italian Forum on Ambient Assisted Living, ForitAAL 2016
ita
2016
ACERBI, GIORGIA; ROVINI, Erika; BETTI, STEFANO; Tirri, Antonio; Rã³nai, Judit Flóra; Sirianni, Antonella; Agrimi, Jacopo; Eusebi, Lorenzo; CAVALLO, F...espandi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1210757
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