日托中心轻度至中度认知障碍患者与社交护理机器人的互动评估:试点研究

IF 3.8 2区 计算机科学 Q2 ROBOTICS International Journal of Social Robotics Pub Date : 2024-02-21 DOI:10.1007/s12369-024-01106-4
María Trinidad Rodríguez-Domínguez, María Isabel Bazago-Dómine, María Jiménez-Palomares, Gerardo Pérez-González, Pedro Núñez, Esperanza Santano-Mogena, Elisa María Garrido-Ardila
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引用次数: 0

摘要

随着痴呆症导致的日常功能障碍不断加剧,社交机器人等利用先进技术的新型认知刺激技术应运而生。本研究探讨了 EBO 社交护理机器人与西班牙埃斯特雷马杜拉省卡塞雷斯日托中心患者的互动水平。研究采用系统视频分析作为互动评估方法。这项观察性试点研究的对象是在AZTIDE社会健康中心接受认知疗法的65岁以上轻度至中度认知障碍患者(明尼苏达州考试21分)。每位参与者接受了两次10-15分钟的个性化治疗,模仿绿野仙踪技术,人类操作员的指令由EBO机器人在不知不觉中执行。六名参与者都与机器人保持了完全的目光接触,83.3%的互动记录了最大注意力。参与者感到舒适和平静,并将专注度和自然度等对话因素评为 "良好 "或 "优秀"。与EBO机器人的高互动水平表明,它是对轻度至中度认知障碍患者进行认知刺激的一种很有前途的工具。系统性的视频评估在评估用户与机器人的互动方面似乎也很有效,因此强调了其在未来社交机器人研究中的潜在用途。
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Interaction Assessment of a Social-Care Robot in Day center Patients with Mild to Moderate Cognitive Impairment: A Pilot Study

As dementia-induced impairments of daily functioning escalate, novel cognitive stimulation techniques utilizing technological advances, like social robots, have surfaced. This study examines the interaction level of the EBO social-care robot with day center patients in Cáceres, Extremadura, Spain. The study uses systematic video analysis as a method of interaction assessment. This observational pilot study was performed on patients above 65 with mild to moderate cognitive impairment (Minimental State Examination \(\ge \) 21) receiving cognitive therapy at the AZTIDE social and health center. Two individualized 10–15 min sessions, replicating the Wizard of Oz technique, were conducted per participant, with the human operator’s commands being unnoticeably executed by the EBO robot. Of the six participants involved, all maintained complete eye contact with the robot, with 83.3\(\%\) of the interactions recording maximum attention. Participants felt comfortable and calm, rating conversational factors such as attentiveness and naturalness as ’good’ or ‘excellent’. The high interaction level with the EBO robot suggests it as a promising tool for cognitive stimulation in patients with mild to moderate cognitive impairment. The systematic video evaluation also appears effective in assessing user–robot interaction, thus underscoring its potential utility in future social robotics research.

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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.
期刊最新文献
Time-to-Collision Based Social Force Model for Intelligent Agents on Shared Public Spaces Investigation of Joint Action in Go/No-Go Tasks: Development of a Human-Like Eye Robot and Verification of Action Space How Non-experts Kinesthetically Teach a Robot over Multiple Sessions: Diversity in Teaching Styles and Effects on Performance The Child Factor in Child–Robot Interaction: Discovering the Impact of Developmental Stage and Individual Characteristics Is the Robot Spying on me? A Study on Perceived Privacy in Telepresence Scenarios in a Care Setting with Mobile and Humanoid Robots
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