发表机构
Institut de Robòtica i Informàtica Industrial, CSIC-UPC; Parc Sanitari Pere Virgili; RE-FiT Barcelona Research Group; Vall d’Hebron Institute of Research; Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet and Stockholm University（工业机器人与信息学研究所，西班牙科学与技术研究委员会 - 加泰罗尼亚理工大学; 圣佩雷维吉利疗养院; 巴塞罗那RE-FiT研究小组; 瓦尔德希伯伦研究院; 衰老研究中心，神经生物学、护理科学与社会系（NVS），卡罗林斯卡学院和斯德哥尔摩大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对老年人虚弱评估资源密集且易忽略生物力学指标的问题，提出用行为树架构的机器人框架，通过视觉跟踪评估临床测试。经现场评估，该框架能提供可靠客观的评估，还可收集相关移动性指标。
AI 中文摘要
虚弱评估对评估老年人不良事件风险及健康和社会护理需求至关重要，但管理资源密集且依赖粗略临床结果，可能忽略功能衰退的生物力学指标。为此，我们提出一个机器人框架，引导老年人通过标准化虚弱和跌倒风险测试，同时获取临床评分和其他与虚弱相关的指标，深入了解用户状况。该系统使用行为树架构协调感知、决策、交互和测量模块，利用基于视觉的骨架跟踪评估既定临床测试。该框架与医疗专业人员共同设计，并在康复中心研究实验室对81名老年人进行了为期六个月的现场评估。将机器人得出的测量结果与治疗师评估及临床参考仪器进行比较。结果显示，大多数测试完成时间和步态相关参数一致性极佳（ICC>0.9），机器人与治疗师的总体SPPB评分一致性较高（k = 0.67），与IMU的一致性中等（k = 0.55）。研究结果表明，社交机器人可在医疗环境中提供可靠、客观的虚弱评估，同时能收集超越传统结果的相关移动性指标。
英文摘要
Frailty assessments are crucial to evaluate the risk of adverse events and the health and social care needs of older adults, yet their administration remains resource-intensive and typically relies on coarse clinical outcomes, such as task completion times, which may overlook biomechanical indicators of functional decline. To address this, we present a robotic framework that guides older adults through standardised frailty and fall-risk tests while capturing clinical scores and additional frailty-related metrics, offering a deeper insight into a user's condition. The system uses a Behaviour Tree architecture that coordinates perception, decision-making, interaction, and measurement modules. Using vision-based skeleton tracking, the robot evaluates established clinical tests, including the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG). The framework was co-designed with healthcare professionals and evaluated in situ during six months in a rehabilitation centre's research lab with N=81 older adults. Robot-derived measurements were compared against therapist assessments and clinical reference instruments, including a gait analysis walkway and an inertial measurement unit (IMU). Results showed excellent agreement for most test completion times and gait-related parameters ($ICC > 0.9$). And, substantial agreement for the overall SPPB score comparing the robot and the therapist ($k = 0.67$) and moderate agreement comparing the robot and the IMU ($k=0.55$). The findings highlight that social robots can provide reliable and objective frailty assessments in healthcare settings while enabling the collection of relevant mobility indicators beyond conventional outcomes.
CommentsThis work has been submitted to the IEEE for possible publication
