SCH: INT: Collaborative Research: Aging In Place Through Enhanced Mobility and Social Connectedness: An Integrated Robot and Wearable Sensor Approach

“居家养老”的概念，即利用先进技术改善老年人在家中的健康和福祉，已在国外流行起来，以降低成本，并使老年人在社区中享有晚年生活的尊严。该项目将使用一个由移动机器人和智能鞋垫传感器组成的综合自主系统，帮助老年人独立生活在自己的家中，并与社区互动。该系统最初将有两个目标：支持锻炼和加强社会联系。目标运动是步行，这是老年人最喜欢和最容易的运动方式。有规律的步行锻炼可以增强平衡感，增强肌肉力量，减少跌倒的风险。该系统引导个人进行定期步行锻炼，自主评估步态状态，并提供实时个性化反馈，以吸引老年人参与锻炼。该机器人还将用于通过虚拟连接将老年人与家人和朋友联系起来。项目团队将在纽约市的一家老年中心评估该系统，使用客观和主观的绩效标准来衡量老年人对该系统的体验。这个项目符合国家利益，因为集成的社会辅助机器人和可穿戴传感器系统增强了老年人的行动能力和社会联系，从而改善了他们的健康和福祉。该项目将包括一个教育部分，为研究生和本科生提供工程和研究方法培训，并为中学生和高中生提供STEM推广。将进一步努力吸引和留住妇女和代表性不足的少数民族从事科学和工程事业。本研究调查了人-机器人-传感器的交互作用，旨在通过使用辅助服务机器人来增强老年人的移动性和社会联系。开发的方法包括结合机器人机载图像传感器的传感能力和智能鞋垫的自主步态分析，通过参数化和基于学习的校准模型。利用逆强化学习探索机器人运动规划的成本函数表示。动态递归神经网络和振动触觉节奏刺激在人机协作行走任务中的应用。该项目还研究了自主任务调度的使用，通过远程呈现机器人技术来增加社会联系。最后，采用客观和主观绩效标准，在某老年中心对综合系统进行实施和实验测试。该项目提供了一种集成机器人和可穿戴传感器的解决方案，以增强移动性和社会联系，填补了原地老龄化研究的空白。开发的方法将在开源平台上实施，实验和评估数据将供公众使用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The concept of "aging in place", using advanced technology to improve the health and well-being of older adults at home, has become popular as away to reduce costs and allow older adults the dignity of living their final years in the community. This project will use an integrated autonomous system that consists of a mobile robot and smart insole sensors to assist older adults to independently live in their own homes and interact with their communities. The system will have two initial goals: supporting exercise and enhancing social connections. The target exercise is walking, the most preferred and accessible exercise modality among older adults. Regular walking exercises may result in enhanced balance, increased muscle strength, and reduced risk of falling. The system guides individuals in regular walking exercises, autonomously assesses gait states, and provides real-time personalized feedback to engage older adults into the exercise. The robot will also be used to connect older adults with family and friends through a virtual connection. The project team will evaluate the system at a senior center in New York City using objective and subjective performance criteria measuring older adults' experiences with the system. This project serves the national interest because the integrated social assistive robot and wearable sensor system enhances mobility and social connectedness of older adults thus should improve their health and well-being. The project will involve an educational component that provides engineering and research method training to graduate and undergraduate students, as well as STEM outreach to middle and high-school students. Additional efforts will be made to attract and retain women and underrepresented minorities into careers in science and engineering.This research investigates human-robot-sensor interaction, and aims to enhance mobility and social connectedness of older adults through the use of an assistive service robot. Methods to be developed include autonomous gait analysis combining sensing capability of robot onboard image sensors and the smart insoles through parametric and learning-based calibration models. The use of inverse reinforcement learning to explore cost function representation for robot motion planning. The use of dynamic recurrent neural networks and vibrotactile rhythmic stimuli for collaborative human-robot walking tasks. The project also examines the use of autonomous task scheduling to increase social contacts through telepresence robotic techniques. Finally, the implementation and experimental testing of the integrated system will be conducted in a senior center using objective and subjective performance criteria. The project fills a gap in aging-in-place research by providing an integrated robot and wearable sensor solution for enhancement of mobility and social connectedness. The developed methods will be implemented on open-source platforms, and the experimental and evaluation data will be made available for public use.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.