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

SCH：INT：协作研究：通过增强移动性和社交联系进行就地老龄化：集成机器人和可穿戴传感器方法

基本信息

批准号：
1838799
负责人：
Yi Guo
金额：
$ 92.72万
依托单位：
Stevens Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-15 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838799&HistoricalAwards=false
关键词：
SCH INT Collaborative Research Aging

项目摘要

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.

“衰老”的概念是利用先进的技术来改善家庭中老年人的健康和福祉，以降低成本并允许老年人在社区中过最后几年的尊严。该项目将使用一个集成的自主系统，该系统由移动机器人和智能鞋垫传感器组成，以帮助老年人独立居住在自己的家中并与社区互动。该系统将有两个最初的目标：支持锻炼和增强社交联系。目标运动是步行，这是老年人中最偏爱和最容易获得的运动方式。定期步行运动可能会导致平衡增强，肌肉力量的增加以及降低的风险降低。该系统指导个人进行常规步行练习，自主评估步态状态，并提供实时个性化反馈，以使老年人参与演习。该机器人还将通过虚拟连接将老年人与家人和朋友联系起来。项目团队将使用客观和主观的绩效标准在纽约市的一个高级中心评估该系统，以衡量老年人在系统中的经验。该项目符合国家的利益，因为综合的社会辅助机器人和可穿戴传感器系统可以增强老年人的流动性和社会联系，因此应改善其健康和福祉。该项目将涉及一个教育组成部分，该教育组成部分为研究生和本科生提供工程和研究方法培训，以及与中学和高中生的STEM宣传。将采取额外的努力来吸引和保留妇女和代表性不足的少数群体进入科学和工程学的职业。这项研究调查了人类机器人传感器的互动，旨在通过使用辅助服务机器人来增强老年人的流动性和社会联系。要开发的方法包括通过参数和基于学习的校准模型结合机器人图像传感器的传感能力和智能鞋垫的自主步态分析。使用逆增强学习来探索机器人运动计划的成本函数表示。动态复发性神经网络和颤振有节奏的刺激的使用用于协作人类手机步行任务。该项目还研究了使用自主任务计划来通过网状机器人技术来增加社交联系。最后，将使用客观和主观性能标准在高级中心进行集成系统的实施和实验测试。该项目通过提供集成的机器人和可穿戴传感器解决方案来增强移动性和社会连接性，从而填补了现场研究的空白。开发的方法将在开源平台上实施，并将提供实验和评估数据供公众使用。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Pedestrian Flow Optimization to Reduce the Risk of Crowd Disasters Through Human–Robot Interaction

DOI：
10.1109/tetci.2019.2930249
发表时间：
2020-06
期刊：
IEEE Transactions on Emerging Topics in Computational Intelligence
影响因子：
5.3
作者：
Chao Jiang;Z. Ni;Yi Guo;Haibo He
通讯作者：
Chao Jiang;Z. Ni;Yi Guo;Haibo He

Improving the Accuracy of Wearable Sensors for Human Locomotion Tracking Using Phase-Locked Regression Models

DOI：
10.1109/icorr.2019.8779428
发表时间：
2019-01-01
期刊：
2019 IEEE 16TH INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR)
影响因子：
0
作者：
Duong, Ton T. H.;Zhang, Huanghe;Zanotto, Damiano
通讯作者：
Zanotto, Damiano

Learning Decentralized Control Policies for Multi-Robot Formation

DOI：
10.1109/aim.2019.8868898
发表时间：
2019-01-01
期刊：
2019 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM)
影响因子：
0
作者：
Jiang, Chao;Chen, Zhuo;Guo, Yi
通讯作者：
Guo, Yi

Optimization of Merging Pedestrian Flows Based on Adaptive Dynamic Programming