A Wearable System for Stress Detection Through Physiological Data Analysis.

Giorgia Acerbi,Erika Rovini,Stefano Betti,Antonio Tirri, Judit Flóra Rónai, Antonella Sirianni,Jacopo Agrimi,Lorenzo Eusebi,Filippo Cavallo

AMBIENT ASSISTED LIVING(2017)

引用 18|浏览2
暂无评分
摘要
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.
更多
查看译文
关键词
Stress monitoring,Stress induction test,Heart rate variability,Galvanic skin response,Feature extraction,Psychometric instruments,Clusterization algorithms
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要