I-Corps: Remote Health Monitoring from Wearable Antenna Measurements

I-Corps：通过可穿戴天线测量进行远程健康监测

• 批准号: 1938748
• 负责人: Yang Li
• 金额: $ 5万
• 依托单位: Baylor University
• 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: 2019-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1938748&HistoricalAwards=false
• 关键词: Corps; Remote; Health; Monitoring; Wearable

The broader impact/commercial potential of this I-Corps project is significant as the proposed antenna measurement system and deep learning classification algorithms can be integrated with 5G mobile devices and provide real-time, continuous tracking and analysis of a wide range of potential activities. The technology will potentially benefit a diverse population including, but not limited to, tracking elderly people at home or in assisted living facilities, soldiers in the battlefield, and athletes in training or competition. The number of connected wearable devices worldwide is expected to surpass 1.1 billion by the year of 2022 and become a $27 billion market. The proposed approach is adaptive and scalable as more and more wearable devices are being deployed in the era of internet of things (IoT).This I-Corps project aims to enable dual-use of antennas embedded inside wearable devices for both wireless communication and motion sensing purposes. Recent research findings demonstrate that the input reflection coefficient from an on-body antenna exhibits unique patterns for different motions and can be used for high fidelity human activity classification as an integrated measurement system. It does not require integration of specialized motion sensors into wearable devices, which can reduce the complexity of the system design, the overall power consumption, and the cost. It can monitor both large-scale activities such as walking and small-scale activities such as finger movements, and can operate in both indoor and outdoor environments. The measurement data can be trained and tested by a customized deep convolutional neural network application to provide high-fidelity human activity classification results, realizing the goal of continuously, remote, user-dependent health monitoring.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/商业潜力是重要的，因为拟议的天线测量系统和深度学习分类算法可以与5G移动的设备集成，并提供对各种潜在活动的实时，连续跟踪和分析。该技术将潜在地使不同的人群受益，包括但不限于跟踪家中或辅助生活设施中的老年人，战场上的士兵以及训练或比赛中的运动员。到2022年，全球联网可穿戴设备的数量预计将超过11亿，成为270亿美元的市场。随着物联网时代越来越多的可穿戴设备被部署，所提出的方法具有自适应性和可扩展性。I-Corps项目旨在实现可穿戴设备中嵌入的天线的双重用途，用于无线通信和运动传感目的。最近的研究结果表明，从一个身体上的天线的输入反射系数表现出独特的模式，为不同的运动，并可用于高保真人体活动分类作为一个集成的测量系统。它不需要将专门的运动传感器集成到可穿戴设备中，这可以降低系统设计的复杂性、整体功耗和成本。它既可以监测步行等大规模活动，也可以监测手指运动等小规模活动，并且可以在室内和室外环境中运行。测量数据可以通过定制的深度卷积神经网络应用程序进行训练和测试，以提供高保真的人类活动分类结果，实现连续，远程，用户依赖的健康监测目标。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。