Lee Miran, Tran Dinh Tuan, Lee Joo-Ho
Advanced Intelligent System Laboratory, Graduate School of Information Science and Engineering, Ritsumeikan University, Shiga, Japan.
Advanced Intelligent System Laboratory, Faculty of Information Science and Engineering, Ritsumeikan University, Shiga, Japan.
Front Robot AI. 2021 Apr 29;8:632015. doi: 10.3389/frobt.2021.632015. eCollection 2021.
As the elderly population increases, the importance of the caregiver's role in the quality of life of the elderly has increased. To achieve effective feedback in terms of care and nursing education, it is important to design a robot that can express emotions or feel pain like an actual human through visual-based feedback. This study proposes a care training assistant robot (CaTARo) system with 3D facial pain expression that simulates an elderly person for improving the skills of workers in elderly care. First, in order to develop an accurate and efficient system for elderly care training, this study introduces a fuzzy logic-based care training evaluation method that can calculate the pain level of a robot for giving the feedback. Elderly caregivers and trainees performed the range of motion exercise using the proposed CaTARo. We obtained quantitative data from CaTARo, and the pain level was calculated by combining four key parameters using the fuzzy logic method. Second, we developed a 3D facial avatar for use in CaTARo that is capable of expressing pain based on the UNBC-McMaster Pain Shoulder Archive, and we then generated four pain groups with respect to the pain level. To mimic the conditions for care training with actual humans, we designed the system to provide pain feedback based on the opinions of experts. The pain feedback was expressed in real time by using a projector and a 3D facial mask during care training. The results of the study confirmed the feasibility of utilizing a care training robot with pain expression for elderly care training, and it is concluded that the proposed approach may be used to improve caregiving and nursing skills upon further research.
随着老年人口的增加，照顾者在老年人生活质量方面的作用变得更加重要。为了在护理教育方面实现有效的反馈，设计一种能够通过基于视觉的反馈像真实人类一样表达情感或感受疼痛的机器人非常重要。本研究提出了一种具有3D面部疼痛表情的护理训练辅助机器人（CaTARo）系统，该系统模拟老年人以提高老年护理工作者的技能。首先，为了开发一个准确且高效的老年护理训练系统，本研究引入了一种基于模糊逻辑的护理训练评估方法，该方法可以计算机器人的疼痛程度以提供反馈。老年护理人员和学员使用所提出的CaTARo进行了关节活动度练习。我们从CaTARo获得了定量数据，并使用模糊逻辑方法结合四个关键参数计算了疼痛程度。其次，我们为CaTARo开发了一个3D面部虚拟形象，它能够基于UNBC - 麦克马斯特疼痛肩部档案库表达疼痛，然后我们根据疼痛程度生成了四个疼痛组。为了模拟与真实人类进行护理训练的条件，我们设计该系统根据专家意见提供疼痛反馈。在护理训练期间，通过投影仪和3D面部面具实时表达疼痛反馈。研究结果证实了使用具有疼痛表达功能的护理训练机器人进行老年护理训练的可行性，并得出结论，在进一步研究后，所提出的方法可用于提高护理和照料技能。
