Robot-Mediated Nudges for Workplace Health: Not a One-Size-Fits-All Modeling Problem

IF 3.8 2区 计算机科学 Q2 ROBOTICS
Rhian C. Preston, Kenna Dinsdale, Madison R. Shippy, Naomi T. Fitter
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Abstract

Prolonged sedentary behavior in the vast population of office and remote workers leads to increased cardiovascular and musculoskeletal health challenges, and existing solutions for encouraging breaks are either costly health coaches or notification systems that are easily ignored. A socially assistive robot (SAR) for promoting healthy workplace practices could provide the physical presence of a health coach along with the scalability of a notification system. To investigate the impact of such a system, we implemented a SAR as an alternative break-taking support solution and examined its impact on individual users’ break-taking habits over relatively long-term deployments. We conducted an initial two-month-long study (N = 7) to begin to understand the robot’s influence beyond the point of novelty, and we followed up with a week-long data collection (N = 14) to augment the dataset size. The resulting data was used to inform a robot behavior model and formulate possible methods of personalizing robot behaviors. We found that uninterrupted sitting time tended to decrease with our SAR intervention. During model formulation, we found participant responsiveness to the break-taking prompts could be classified into three archetypes and that archetype-specific adjustments to the general model led to improved system success. These results indicate that break-taking prompts are not a one-size-fits-all problem, and that even a small dataset can support model personalization for improving the success of assistive robotic systems.

Abstract Image

以机器人为媒介的工作场所健康指导:并非 "一刀切 "的建模问题
广大办公室和远程工作者长期久坐不动会导致心血管和肌肉骨骼健康问题日益严重,而现有的鼓励休息的解决方案要么是昂贵的健康指导员,要么是容易被忽视的通知系统。用于促进工作场所健康行为的社交辅助机器人(SAR)可以提供健康指导员的实际存在以及通知系统的可扩展性。为了研究这种系统的影响,我们将社交辅助机器人作为一种替代性休息支持解决方案,并在相对长期的部署过程中研究了它对个人用户休息习惯的影响。我们首先进行了为期两个月的研究(N = 7),以了解机器人在新奇感之外的影响,随后又进行了为期一周的数据收集(N = 14),以扩大数据集的规模。我们利用收集到的数据建立了机器人行为模型,并制定了个性化机器人行为的可行方法。我们发现,在我们的 SAR 干预措施下,不间断坐着的时间往往会减少。在建立模型的过程中,我们发现参与者对休息提示的反应可分为三种原型,对一般模型进行特定原型调整可提高系统成功率。这些结果表明,断食提示并不是一个放之四海而皆准的问题,即使是小规模的数据集也能支持模型个性化,从而提高辅助机器人系统的成功率。
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来源期刊
CiteScore
9.80
自引率
8.50%
发文量
95
期刊介绍: Social Robotics is the study of robots that are able to interact and communicate among themselves, with humans, and with the environment, within the social and cultural structure attached to its role. The journal covers a broad spectrum of topics related to the latest technologies, new research results and developments in the area of social robotics on all levels, from developments in core enabling technologies to system integration, aesthetic design, applications and social implications. It provides a platform for like-minded researchers to present their findings and latest developments in social robotics, covering relevant advances in engineering, computing, arts and social sciences. The journal publishes original, peer reviewed articles and contributions on innovative ideas and concepts, new discoveries and improvements, as well as novel applications, by leading researchers and developers regarding the latest fundamental advances in the core technologies that form the backbone of social robotics, distinguished developmental projects in the area, as well as seminal works in aesthetic design, ethics and philosophy, studies on social impact and influence, pertaining to social robotics.
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