Stress may be defined as the reaction of the body to regulate itself to changes within the environment through mental, physical, or emotional responses. Recurrent episodes of acute stress can disturb the physical and mental stability of a person. This subsequently can have a negative effect on work performance and in the long term can increase the risk of physiological disorders like hypertension and psychological illness such as anxiety disorder. Psychological stress is a growing concern for the worldwide population across all age groups. A reliable, cost-efficient, acute stress detection system could enable its users to better monitor and manage their stress to mitigate its long-term negative effects. In this article, we will review and discuss the literature that has used machine learning based approaches for stress detection. We will also review the existing solutions in the literature that have leveraged the concept of edge computing in providing a potential solution in real-time monitoring of stress.

中文翻译：

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基于机器学习的实时压力监控解决方案

压力可以定义为身体通过精神，身体或情感反应来调节自身对环境变化的反应。急性压力的反复发作会干扰一个人的身心稳定。因此，这可能会对工作表现产生负面影响，并且从长远来看会增加诸如高血压之类的生理疾病和诸如焦虑症之类的心理疾病的风险。对于所有年龄段的全球人口来说，心理压力都日益引起人们的关注。一个可靠，具有成本效益的急性压力检测系统可以使用户更好地监控和管理其压力，以减轻其长期的负面影响。在本文中，我们将回顾和讨论使用基于机器学习的方法进行压力检测的文献。