论文标题

人力压力评估:对使用可穿戴传感器和不可磨损技术的方法的全面综述

Human Stress Assessment: A Comprehensive Review of Methods Using Wearable Sensors and Non-wearable Techniques

论文作者

Arsalan, Aamir, Majid, Muhammad, Nizami, Imran Fareed, Manzoor, Waleed, Anwar, Syed Muhammad, Ryu, Jihyoung

论文摘要

本文对涵盖文献中可用的大量主观和客观人力压力检测技术的方法进行了全面综述。测量人类压力反应的方法可能包括主观问卷(由心理学家开发)以及使用可穿戴和不可磨损传感器的数据观察到的客观标记。特别是,基于可穿戴传感器的方法通常使用脑电图,心电图,电肌皮反应,肌电图,电肌电活动,心率,心率变异性和光脑性学术的数据。而基于不可磨损传感器的方法包括分析瞳孔扩张和言语,智能手机数据,眼动,身体姿势和热成像等策略。每当诱发个人,生理,身体或行为改变的个人时,都会有帮助应对手头的挑战。广泛的研究试图通过使用不同种类的心理,生理,身体和行为措施来建立这些压力状况与人类反应之间的关系。受到关于人类压力与这些不同类型标记的关系的确定性判决的启发,本文对人类压力检测方法进行了详细的调查。特别是,我们探讨了如何利用来自各种来源的相关数据从人工智能中受益的压力检测方法。这篇综述将被证明是一份参考文件,将为未来的研究提供指南,从而有效检测人类压力状况。

This paper presents a comprehensive review of methods covering significant subjective and objective human stress detection techniques available in the literature. The methods for measuring human stress responses could include subjective questionnaires (developed by psychologists) and objective markers observed using data from wearable and non-wearable sensors. In particular, wearable sensor-based methods commonly use data from electroencephalography, electrocardiogram, galvanic skin response, electromyography, electrodermal activity, heart rate, heart rate variability, and photoplethysmography both individually and in multimodal fusion strategies. Whereas, methods based on non-wearable sensors include strategies such as analyzing pupil dilation and speech, smartphone data, eye movement, body posture, and thermal imaging. Whenever a stressful situation is encountered by an individual, physiological, physical, or behavioral change is induced which help in coping with the challenge at hand. A wide range of studies has attempted to establish a relationship between these stressful situations and the response of human beings by using different kinds of psychological, physiological, physical, and behavioral measures. Inspired by the lack of availability of a definitive verdict about the relationship of human stress with these different kinds of markers, a detailed survey about human stress detection methods is conducted in this paper. In particular, we explore how stress detection methods can benefit from artificial intelligence utilizing relevant data from various sources. This review will prove to be a reference document that would provide guidelines for future research enabling effective detection of human stress conditions.

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