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人机空间关系对人形机器人参与的人类注意力训练游戏的影响。

Impacts of Human Robot Proxemics on Human Concentration-Training Games with Humanoid Robots.

作者信息

Liu Li, Liu Yangguang, Gao Xiao-Zhi

机构信息

College of Digital Technology and Engineering, Ningbo University of Finance and Economics, Ningbo 315175, China.

College of Finance and Information, Ningbo University of Finance and Economics, Ningbo 315175, China.

出版信息

Healthcare (Basel). 2021 Jul 15;9(7):894. doi: 10.3390/healthcare9070894.

Abstract

The use of humanoid robots within a therapeutic role, that is, helping individuals with social disorders, is an emerging field, but it remains unexplored in terms of concentration training. To seamlessly integrate humanoid robots into concentration games, an investigation into the impacts of human robot interactive proxemics on concentration-training games is particularly important. In the case of an epidemic diffusion especially-for example, during the COVID-19 pandemic-HRI games may help in the therapeutic phase, significantly reducing the risk of contagion. In this paper, concentration games were designed by action imitation involving 120 participants to verify the hypothesis. Action-imitation accuracy, the assessment of emotional expression, and a questionnaire were compared with analysis of variance (ANOVA). Experimental results showed that a 2 m distance and left-front orientation for a human and a robot are optimal for human robot interactive concentration training. In addition, females worked better than males did in HRI imitation games. This work supports some valuable suggestions for the development of HRI concentration-training technology, involving the designs of friendlier and more useful robots, and HRI game scenarios.

摘要

将类人机器人用于治疗目的,即帮助患有社交障碍的个体,这是一个新兴领域,但在注意力训练方面仍未得到探索。为了将类人机器人无缝集成到注意力游戏中,研究人机交互距离对注意力训练游戏的影响尤为重要。在疫情传播的情况下,特别是例如在新冠疫情期间,人机交互游戏可能有助于治疗阶段,显著降低传染风险。在本文中,通过动作模仿设计了注意力游戏,涉及120名参与者以验证该假设。将动作模仿准确性、情感表达评估和一份问卷与方差分析(ANOVA)进行了比较。实验结果表明,人与机器人之间2米的距离和左前方的方向对于人机交互注意力训练是最佳的。此外,在人机交互模仿游戏中,女性的表现优于男性。这项工作为开发人机交互注意力训练技术提供了一些有价值的建议,包括设计更友好、更有用的机器人以及人机交互游戏场景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/210f/8307354/cbd856944042/healthcare-09-00894-g001.jpg

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