A person's behavior significantly influences their health and well-being. It also contributes to the social environment in which humans interact, with cascading impacts to the health and behaviors of others. During social interactions, our understanding and awareness of vital nonverbal messages expressing beliefs, emotions, and intentions can be obstructed by a variety of factors including greatly flawed self-awareness. For these reasons, human behavior is a very important topic to study using the most advanced technology. Moreover, technology offers a breakthrough opportunity to improve people's social awareness and self-awareness through machine-enhanced recognition and interpretation of human behaviors. This paper reviews (1) the social psychology theories that have established the framework to study human behaviors and their manifestations during social interactions and (2) the technologies that have contributed to the monitoring of human behaviors. State-of-the-art in sensors, signal features, and computational models are categorized, summarized, and evaluated from a comprehensive transdisciplinary perspective. This review focuses on assessing technologies most suitable for real-time monitoring while highlighting their challenges and opportunities in near-future applications. Although social behavior monitoring has been highly reported in psychology and engineering literature, this paper uniquely aims to serve as a disciplinary convergence bridge and a guide for engineers capable of bringing new technologies to bear against the current challenges in real-time human behavior monitoring.

中文翻译：

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实时人类行为监测技术的回顾与挑战

一个人的行为会显着影响他们的健康和幸福。它还有助于人类互动的社会环境，对他人的健康和行为产生连锁影响。在社交互动中，我们对表达信念、情感和意图的重要非语言信息的理解和意识可能会受到各种因素的阻碍，包括存在严重缺陷的自我意识。由于这些原因，人类行为是使用最先进技术研究的一个非常重要的课题。此外，技术通过机器增强对人类行为的识别和解释，为提高人们的社会意识和自我意识提供了突破性的机会。本文回顾了 (1) 建立了研究人类行为及其在社会互动中的表现的框架的社会心理学理论，以及 (2) 有助于监测人类行为的技术。从全面的跨学科角度对传感器、信号特征和计算模型方面的最新技术进行分类、总结和评估。本综述重点评估最适合实时监控的技术，同时强调它们在近期应用中的挑战和机遇。尽管社会行为监测在心理学和工程文献中得到了高度的报道，