Hooman Sarvghadi , Andreas Reinhardt , Esther A. Semmelhack
{"title":"A survey of wearable devices to capture human factors for human-robot collaboration","authors":"Hooman Sarvghadi , Andreas Reinhardt , Esther A. Semmelhack","doi":"10.1016/j.pmcj.2025.102048","DOIUrl":null,"url":null,"abstract":"<div><div>Technology has rapidly evolved over the course of the last decades, and drastically transformed our way of life. Robots are no longer just mechanical aides, but have become collaborators on many tasks. Wearable gadgets have become virtually ubiquitous due to their ability to collect data, monitor health parameters, and assist users in various day-to-day tasks. In recent years, there has been a surge in interest around the use of wearable technologies to collect human psychological parameters for human–robot collaboration. With the field of robotics advancing, there is a growing need for robots to interact with humans seamlessly. To achieve this seamless human–robot connection, robots must be able to interpret human emotions and react appropriately. While understanding human emotions and behavior is a complex task in itself, wearable sensor systems contribute valuable insights. This survey provides a comprehensive overview of wearable gadgets and technologies proposed for measuring five key human factors — trust, cognitive workload, stress, safety perception, and fatigue — within the scope of human–robot collaboration, based on the systematic review of papers published between 2015 and the end of 2024 in six major databases. Our analysis indicates that trust and cognitive workload have received greater attention from researchers in recent years, as compared to other human factors. The Empatica E4 wristband, Shimmer3 GSR+ and EPOC X EEG headset are among the most widely used wearable devices, capable of capturing essential physiological parameters widely used for human–robot collaboration, including electrodermal activity, heart rate variability, skin temperature, and electroencephalogram. Besides reviewing the potentials and capabilities of these gadgets, we highlight their shortcomings and offer directions for future research in this domain.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"110 ","pages":"Article 102048"},"PeriodicalIF":3.0000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pervasive and Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574119225000379","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Technology has rapidly evolved over the course of the last decades, and drastically transformed our way of life. Robots are no longer just mechanical aides, but have become collaborators on many tasks. Wearable gadgets have become virtually ubiquitous due to their ability to collect data, monitor health parameters, and assist users in various day-to-day tasks. In recent years, there has been a surge in interest around the use of wearable technologies to collect human psychological parameters for human–robot collaboration. With the field of robotics advancing, there is a growing need for robots to interact with humans seamlessly. To achieve this seamless human–robot connection, robots must be able to interpret human emotions and react appropriately. While understanding human emotions and behavior is a complex task in itself, wearable sensor systems contribute valuable insights. This survey provides a comprehensive overview of wearable gadgets and technologies proposed for measuring five key human factors — trust, cognitive workload, stress, safety perception, and fatigue — within the scope of human–robot collaboration, based on the systematic review of papers published between 2015 and the end of 2024 in six major databases. Our analysis indicates that trust and cognitive workload have received greater attention from researchers in recent years, as compared to other human factors. The Empatica E4 wristband, Shimmer3 GSR+ and EPOC X EEG headset are among the most widely used wearable devices, capable of capturing essential physiological parameters widely used for human–robot collaboration, including electrodermal activity, heart rate variability, skin temperature, and electroencephalogram. Besides reviewing the potentials and capabilities of these gadgets, we highlight their shortcomings and offer directions for future research in this domain.
在过去的几十年里,科技迅速发展,彻底改变了我们的生活方式。机器人不再仅仅是机械助手,而是在许多任务中成为合作者。由于可穿戴设备能够收集数据、监测健康参数并协助用户完成各种日常任务,因此它们几乎无处不在。近年来,人们对使用可穿戴技术来收集人类心理参数以进行人机协作的兴趣激增。随着机器人领域的发展,人们对机器人与人类无缝互动的需求越来越大。为了实现这种无缝的人机连接,机器人必须能够理解人类的情感并做出适当的反应。虽然理解人类的情绪和行为本身就是一项复杂的任务,但可穿戴传感器系统提供了有价值的见解。本调查基于对2015年至2024年底在六个主要数据库中发表的论文的系统综述,全面概述了可穿戴设备和技术,这些设备和技术用于测量人机协作范围内的五个关键人为因素——信任、认知工作量、压力、安全感知和疲劳。我们的分析表明,与其他人为因素相比,信任和认知工作量近年来受到了研究人员的更多关注。Empatica E4腕带、Shimmer3 GSR+和EPOC X EEG耳机是应用最广泛的可穿戴设备,能够捕获广泛用于人机协作的基本生理参数,包括皮电活动、心率变率、皮肤温度和脑电图。除了回顾这些小工具的潜力和能力外,我们还指出了它们的不足之处,并提出了该领域未来的研究方向。
期刊介绍:
As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies.
The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.