arXiv:2601.09838cs.ROcs.HC2026-01

开发可协助儿童康复的社交机器人Mobirobot,支持个性化运动训练。

Interprofessional and Agile Development of Mobirobot: A Socially Assistive Robot for Pediatric Therapy Across Clinical and Therapeutic Settings

  • 通过多学科协作与用户参与,迭代设计出适配临床场景的机器人。
  • 在医院环境中验证了其可用性,用户反馈推动交互与移动功能优化。
  • 适合儿童康复治疗师、研究者及智能医疗系统开发者参考。

社交辅助机器人有望提升儿科临床治疗中的患者参与度。本文介绍的Mobirobot是一款专为创伤、骨折或抑郁障碍患儿设计的康复辅助机器人,支持个性化运动计划。采用敏捷的人本设计方法,临床团队与终端用户全程参与,将机器人整合进真实儿科外科和精神科环境。基于NAO平台,机器人具备简易部署、可调运动程序、互动引导、激励对话及无需编程的图形化监控界面。在医院部署中识别出关键设计需求与可用性限制,利益相关者反馈促使交互设计、运动能力与技术配置的改进。目前正在进行可行性研究,评估接受度、可用性与感知治疗效益,数据收集包括问卷、行为观察与医护人员访谈。结果表明,多专业协同开发能产出适应动态住院环境的社交辅助系统。早期发现强调情境融合、鲁棒性与低侵入设计的重要性。尽管存在传感器局限与患者招募挑战,该平台仍为后续研究与临床应用提供良好基础。

原文摘要 · Abstract (English)

Introduction: Socially assistive robots hold promise for enhancing therapeutic engagement in paediatric clinical settings. However, their successful implementation requires not only technical robustness but also context-sensitive, co-designed solutions. This paper presents Mobirobot, a socially assistive robot developed to support mobilisation in children recovering from trauma, fractures, or depressive disorders through personalised exercise programmes. Methods: An agile, human-centred development approach guided the iterative design of Mobirobot. Multidisciplinary clinical teams and end users were involved throughout the co-development process, which focused on early integration into real-world paediatric surgical and psychiatric settings. The robot, based on the NAO platform, features a simple setup, adaptable exercise routines with interactive guidance, motivational dialogue, and a graphical user interface (GUI) for monitoring and no-code system feedback. Results: Deployment in hospital environments enabled the identification of key design requirements and usability constraints. Stakeholder feedback led to refinements in interaction design, movement capabilities, and technical configuration. A feasibility study is currently underway to assess acceptance, usability, and perceived therapeutic benefit, with data collection including questionnaires, behavioural observations, and staff-patient interviews. Discussion: Mobirobot demonstrates how multiprofessional, stakeholder-led development can yield a socially assistive system suited for dynamic inpatient settings. Early-stage findings underscore the importance of contextual integration, robustness, and minimal-intrusion design. While challenges such as sensor limitations and patient recruitment remain, the platform offers a promising foundation for further research and clinical application.

社交机器人儿童康复人机交互

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。