用机器人非语言信号提升老人护理中的信任感，发现触摸和灯光效果最佳。
Enhancing Human-Robot Interaction in Healthcare: A Study on Nonverbal Communication Cues and Trust Dynamics with NAO Robot Caregivers
- 测试触觉、手势和灯光三种非语言信号对互动的影响。
- 灯光比手势更易被感知且更准确，触觉监测受老人欢迎。
- 长期互动能显著提升信任与共情感，适合持续照护场景。
随着老年人口增加，对人与机器人照护者的需求同步上升。传统人力照护成本高昂，而使用Nao机器人可降低成本并提供帮助。本研究采用混合方法与被试内因子设计，探索非语言沟通方式（触觉、手势、LED灯模式）在健康监测与照护中的有效性。结果显示，参与者对Nao的触觉健康监测评价积极，各项维度得分良好；相较于手部与头部手势，LED灯模式被感知为更有效且更准确；长时间互动与更高的信任度及共情感知相关，表明持续交互对建立信任至关重要。尽管存在局限，研究为类人机器人在老年照护中的应用提供了重要参考。
原文摘要 · Abstract (English)
As the population of older adults increases, so will the need for both human and robot care providers. While traditional practices involve hiring human caregivers to serve meals and attend to basic needs, older adults often require continuous companionship and health monitoring. However, hiring human caregivers for this job costs a lot of money. However, using a robot like Nao could be cheaper and still helpful. This study explores the integration of humanoid robots, particularly Nao, in health monitoring and caregiving for older adults. Using a mixed-methods approach with a within-subject factorial design, we investigated the effectiveness of nonverbal communication modalities, including touch, gestures, and LED patterns, in enhancing human-robot interactions. Our results indicate that Nao's touch-based health monitoring was well-received by participants, with positive ratings across various dimensions. LED patterns were perceived as more effective and accurate compared to hand and head gestures. Moreover, longer interactions were associated with higher trust levels and perceived empathy, highlighting the importance of prolonged engagement in fostering trust in human-robot interactions. Despite limitations, our study contributes valuable insights into the potential of humanoid robots to improve health monitoring and caregiving for older adults.
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