I-Corps: Adaptive Robotic Nursing Assistants for Physical Healthcare Delivery

I-Corps：用于身体保健服务的自适应机器人护理助理

• 批准号: 2016973
• 负责人: Dan Popa
• 金额: $ 5万
• 依托单位: University of Louisville Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016973&HistoricalAwards=false
• 关键词: Corps; Adaptive; Robotic; Nursing; Assistants

The broader impact/commercial potential of this I-Corps project is the development of robotic technologies to assist healthcare workers deliver better and more efficient services to patients in hospitals and nursing home environments. The Bureau of Labor statistics indicates that there are millions of registered nurses in the United States, which makes them the largest workforce providing healthcare. The proposed technology has the potential to augment the nursing workforce and help offset personnel shortages in hospitals, long-term care facilities, and nursing homes. Adaptive robotic nursing assistants may reduce nurses’ exposure to infectious agents, reduce musculoskeletal injuries, and increase job satisfaction by freeing up time spent on item fetching, repetitive measurements of vital signs, and lifting. A robot that can communicate with the electronic health records to document completed tasks may have greater impact by saving nurses’ time devoted to paperwork. With the predicted shortage in nursing workforce, nurse workloads are expected to increase, and robot nursing assistants have the potential to handle some of the physical and administrative nursing tasks. Patients and hospitals may gain in terms of quality of care, prevention of falls, and faster service through automation.This I-Corps project is based on the development of adaptive robotic nursing assistants for physical and administrative tasks in hospital environments. The technology consists of a mobile manipulator with an omni-directional base, a 6-degrees of freedom (DOF) robotic arm, and sensors to assist with nursing scenarios such as sitting and walking with patients. The sensors include both non-contact proximity and contact tactile skins to allow the robot to operate safely in busy healthcare environments while interacting physically with nurses and patients. The technology also incorporates human-machine interfaces (HMIs) that allow users to interact with the robot in an intuitive manner that may be tailored to individual preferences. The proposed technology’s neuroadaptive learning control technology may adapt to each user’s behavior during physical human-robot interaction, ensuring both high quality interaction, programmable adaptive HMI behaviors, and robust performance under operational uncertainties. Using this technology, the robot can navigate the environment, fetch objects, and automate mundane nursing tasks while keeping healthcare workers in the decision loop.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目的更广泛的影响/商业潜力是开发机器人技术，以帮助医疗工作者为医院和疗养院环境中的患者提供更好，更有效的服务。美国劳工局的统计数据显示，美国有数百万注册护士，这使他们成为提供医疗保健的最大劳动力。这项技术有可能增加护理人员，并帮助弥补医院、长期护理机构和疗养院的人员短缺。自适应机器人护理助理可以减少护士接触传染性病原体，减少肌肉骨骼损伤，并通过释放用于物品获取，生命体征重复测量和提升的时间来提高工作满意度。一个可以与电子健康记录进行通信以记录已完成任务的机器人可能会节省护士用于文书工作的时间，从而产生更大的影响。随着护理劳动力的短缺，预计护士的工作量将增加，机器人护理助理有可能处理一些物理和行政护理任务。病人和医院可能会获得护理质量，预防福尔斯，并通过automation.This I-Corps项目更快的服务是基于自适应机器人护理助理在医院环境中的物理和管理任务的发展。该技术由一个带有全方位底座的移动的机械手、一个6自由度（DOF）机械臂和传感器组成，用于辅助护理场景，如与患者一起坐着和行走。传感器包括非接触接近和接触触觉皮肤，以允许机器人在与护士和患者进行物理交互的同时在忙碌的医疗环境中安全地操作。该技术还集成了人机界面（HMI），允许用户以直观的方式与机器人进行交互，可以根据个人偏好进行定制。所提出的技术的神经自适应学习控制技术可以在物理人机交互期间适应每个用户的行为，从而确保高质量的交互、可编程的自适应HMI行为以及在操作不确定性下的鲁棒性能。利用这项技术，机器人可以在环境中导航，抓取物体，并自动执行日常护理任务，同时让医护人员参与决策。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。