PFI:BIC - Adaptive Robotic Nursing Assistants for Physical Tasks in Hospital Environments

PFI:BIC - 在医院环境中执行体力任务的自适应机器人护理助理

• 批准号: 1534124
• 负责人: Dan Popa
• 金额: $ 99.99万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1534124&HistoricalAwards=false
• 关键词: PFI; BIC; Adaptive; Robotic; Nursing

This Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) project aims to provide next-generation assistive robots to support the activities of hospital-based registered nurses (RNs). There are nearly three million registered nurses employed in the United States, making them the largest pool of healthcare providers in the country. Technology that affects the performance of this large labor pool cannot fail to have impact. Due to advancements in robotics and computer technology, access to intelligent communication, sensing, and computing hardware is on the cusp of becoming common--not only for healthcare professionals, but also for patients themselves. The project led by The University of Texas at Arlington will focus on the creation of new design tools that can configure the hardware and software of adaptive robotic nursing assistants (ARNA). ARNA will be specifically designed to assist nurses in healthcare facilities with simple tasks such as, lift assistance, delivery of everyday lightweight objects (medicine, medical wearable equipment), and some physical assistance with movement of heavier objects, such as furniture, gurneys, and the patients themselves. The design and engineering innovations resulting from insights gained in this project may have great value deployed as products in broader consumer markets in addition to hospitals. Examples include in-home service and assistive robots, robots for assistance in public venues, and co-Robot manufacturing where humans are in close proximity to robot workers. The improved understanding of human-robot and nurse-robot interaction could represent enabling technology that will facilitate research breakthroughs and increase productivity and social acceptance of robotics. The research will also advance the understanding of the perceptual effects of robot design aesthetics and interfaces.The proposed Adaptive Robotic Nurse Assistants will navigate cluttered hospitals, while equipped with multi-modal skin sensors that can anticipate nurse intent, automate mundane low-level tasks, but keep nurses in the decision loop. Modular and strong hardware will be deployed in reconfigurable platforms specially designed for nurse physical assistance. Adaptive human-machine interfaces will play a key role in this project, as these interfaces directly impact the ability of robots to help nurses in a dynamic, unstructured environment. Rather than pre-programming robot behaviors, learning algorithms will be used so that robots adapt to human preferences. Two leading applications are envisioned for feasibility evaluation by quantitative and qualitative metrics, including patient sitters and walkers. The sitter robot will take vital sign measurements, evaluate risk from patient movement and pose, and provide continuous observation of patients and feedback to and from nurses. The walker robot will assist nurses and patients by providing partial balance support, navigating cluttered environments, and assisting with medical equipment transportation.The lead institution is the University of Texas at Arlington with its multidisciplinary departments including the College of Engineering, College of Nursing, and the University of Texas at Arlington Research Institute (UTARI). Primary industrial partners include QinetiQ-North America (Waltham, MA), a large corporation specializing in unmanned systems, and RE2 (Pittsburgh, PA), a small business specializing in modular robotic manipulators that will contribute unique battle-tested hardware and systems engineering. In-hospital testing and evaluation of the proposed robots will be carried out by nurse researchers at the University of Texas at Arlington College of Nursing and Texas Health Resources (Dallas-Fort Worth, TX), a large healthcare provider.

这种创新合作伙伴关系：建筑创新能力（PFI：BIC）项目旨在提供下一代辅助机器人，以支持基于医院的注册护士（RNS）的活动。在美国，有近300万名注册护士，使其成为该国最大的医疗保健提供者。影响这个大劳动池表现的技术不会产生影响。由于机器人技术和计算机技术方面的进步，获得智能沟通，感应和计算硬件的访问是变得普遍的风口，这不仅是医疗保健专业人员，而且对于患者本身而言。由德克萨斯大学阿灵顿分校领导的项目将着重于创建可以配置自适应机器人护理助理（ARNA）的硬件和软件的新设计工具。 ARNA将被专门设计，以帮助护士在医疗机构中完成简单任务，例如，提升援助，日常轻量级物体（医学，医疗可穿戴设备），以及在较重物体的移动方面进行的一些身体援助，例如家具，gurneys和患者本身。除医院外，该项目中获得的见解所产生的设计和工程创新可能还具有广泛的消费市场中的产品。例如，包括家庭服务和辅助机器人，在公共场所提供援助的机器人以及人类与机器人工人非常接近的共同机器人制造。对人类机器人和护士机器人互动的增进理解可以代表有助于研究突破并提高生产力和社会接受机器人技术的技术。这项研究还将提高对机器人设计美学和界面的感知影响的理解。拟议的自适应机器人护士助手将导航混乱的医院，同时配备有多模式的皮肤传感器，可以预期护士的意图，自动化自动化的平凡的低级任务，但请在决策过程中保持护士。模块化硬件将部署在专门为护士身体援助的可重构平台中。自适应人机界面将在该项目中发挥关键作用，因为这些界面直接影响机器人在动态，非结构化的环境中帮助护士的能力。将使用学习算法而不是预先编程的机器人行为，以使机器人适应人类的偏好。设想通过定量和定性指标（包括病人的保姆和步行者）进行两项主要应用程序，以评估可行性。保姆机器人将进行生命体征测量，评估患者运动和姿势的风险，并不断观察患者以及对护士的反馈。 Walker机器人将通过提供部分平衡支持，导航混乱的环境并协助医疗设备运输来帮助护士和患者。领导机构是德克萨斯大学阿灵顿分校的多学科系，包括工程学学院，护理学院，以及德克萨斯大学的德克萨斯大学阿灵顿研究所（UTARI）（UTARI）。主要工业合作伙伴包括一家专门从事无人系统的大型公司Qinetiq-North America（马萨诸塞州沃尔瑟姆）和RE2（宾夕法尼亚州匹兹堡），这是一家专门从事模块化机器人操纵器的小型企业，将为独特的战斗测试硬件和系统工程提供独特的机器人操纵器。德克萨斯大学阿灵顿护理学院和德克萨斯州卫生资源学院（达拉斯 - 沃思沃思，德克萨斯州达拉斯 - 沃思）的护士研究人员将对拟议机器人进行院内测试和评估。