CAREER: Multi-Utility Textile Electromagnetics for Motion Capture and Tissue Monitoring Cyber-Physical Systems
职业:用于运动捕捉和组织监测网络物理系统的多功能纺织电磁学
基本信息
- 批准号:2042644
- 负责人:
- 金额:$ 52.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-10-01 至 2026-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Wearable sensors show much promise for medical, sports, defense, emergency, and consumer applications, but are currently limited to obtrusive implementations. Akin to the evolution of cell phones that evolved from foot-long prototypes to recent smart devices, next-generation wearables are envisioned to be seamlessly embedded in fabrics. This CAREER project aims to understand the unique challenges of operating such textile sensors “in-the-wild” and to empower their reliable operation via closed-loop interaction among fabrics, electronics, and humans. To serve as a model and to inspire new applications, the project focuses on new classes of functionalized garments that can seamlessly monitor kinematics and/or tissue abnormalities with unique advantages over the state-of-the-art. Concurrently, the integrated education/outreach efforts aim to increase student and public exposure to bio-electromagnetics that are now confined to specialized research, yet can enable interdisciplinary training for all via appealing activities with direct societal impact.This CAREER project will pioneer a design, modeling, and implementation framework that reconciles human-in-the-loop Cyber-Physical Systems (CPS) with conductive e-textile sensors operating in complex (human wearing a sensing fabric) and dynamic (real-world) environments. Cognitive and fully-adaptive e-textile CPS are proposed that: (a) are cognizant of inputs received by the wearer, the fabric, and the environment, and (b) integrate agility in both the cyber and physical sides for closed-loop adaptability on the fly. In turn, potentials in optimizing performance, minimizing resources, and enhancing opportunities for myriads of human-in-the-loop CPS are envisioned to be significant. Without loss of generality, focus is on a novel-multi-utility sensor that addresses two of the most challenging sensing modalities in the area of wearables, i.e., motion capture and tissue abnormality monitoring. These modalities may be individually or concurrently employed to create models for dense-data (motion captured on the go), sparse-data (tissues monitored over sparse intervals), and context-aware (both of the above) human-in-the-loop CPS. As a case study, a novel CPS will be progressively designed – from concept to in vivo testing – to improve outcomes after anterior cruciate ligament reconstruction.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.
可穿戴传感器在医疗、体育、国防、紧急情况和消费者应用方面显示出巨大的前景,但目前仅限于引人注目的实现,就像手机从一英尺长的原型发展到最新智能设备的发展一样,下一代可穿戴设备也在不断发展。该 CAREER 项目旨在了解“野外”操作此类纺织品传感器的独特挑战,并通过织物、电子设备和人类之间的闭环交互来实现其可靠运行。作为一个模型并激发新的应用,该项目重点关注新型功能化服装,这些服装可以无缝监测运动学和/或组织异常,与最先进的技术相比具有独特的优势,同时进行综合教育/推广工作。旨在增加学生和公众对生物电磁学的接触,生物电磁学目前仅限于专业研究,但可以通过具有直接社会影响的有吸引力的活动为所有人提供跨学科培训。该职业项目将开创一个协调一致的设计、建模和实施框架提出了具有在复杂(人类穿着传感织物的人类)和动态(现实世界)环境中运行的导电电子纺织品传感器的人在环网络物理系统(CPS)认知和完全自适应的电子纺织品CPS。 (a) 识别穿着者、织物和环境接收到的输入,以及 (b) 集成网络和物理方面的敏捷性,以实现动态闭环适应性。在优化性能、最小化资源以及增强无数人在环 CPS 的机会方面的潜力预计将是巨大的,在不失一般性的情况下,重点是解决两个最具挑战性的新型多功能传感器。可穿戴设备领域的传感模式,即运动捕捉和组织异常监测这些模式可以单独或同时用于创建密集数据(移动中捕捉的运动)、稀疏数据的模型。 (在稀疏间隔内监测组织)和情境感知(以上两者)人机循环 CPS 作为案例研究,将逐步设计一种新型 CPS - 从概念到体内测试 - 以改善结果。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。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Multi-Utility Wearable Sensors for Motion Capture and Tissue Imaging
用于运动捕捉和组织成像的多用途可穿戴传感器
- DOI:10.23919/at-ap-rasc54737.2022.9814267
- 发表时间:2022-01
- 期刊:
- 影响因子:0
- 作者:Islam, Asiful;Mishra, Vigyanshu;Dalisky, Zeke;Kiourti, Asimina
- 通讯作者:Kiourti, Asimina
Denoising Textile Kinematics Sensors: A Machine Learning Approach
纺织运动学传感器去噪:一种机器学习方法
- DOI:
- 发表时间:1970-01-01
- 期刊:
- 影响因子:0
- 作者:Yuxuan Han;Vigyanshu Mishra;A. Kiourti
- 通讯作者:A. Kiourti
Wearable Loop Sensor for Unambiguous and High-Resolution Joint Kinematics Monitoring
可穿戴环路传感器可实现明确且高分辨率的关节运动学监控
- DOI:10.1109/jerm.2022.3175073
- 发表时间:2022-01
- 期刊:
- 影响因子:0
- 作者:Mishra, Vigyanshu;Kiourti, Asimina
- 通讯作者:Kiourti, Asimina
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Asimina Kiourti其他文献
Asimina Kiourti的其他文献
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{{ truncateString('Asimina Kiourti', 18)}}的其他基金
High Accuracy Image Reconstruction Using Microwave Measurements from Bio-Matched Antennas and Deep Learning: A Synthesized X-ray Computed Tomography Approach
使用生物匹配天线和深度学习的微波测量进行高精度图像重建:一种合成 X 射线计算机断层扫描方法
- 批准号:
2244882 - 财政年份:2023
- 资助金额:
$ 52.77万 - 项目类别:
Standard Grant
Collaborative Research: Cognitive Workload Classification in Dynamic Real-World Environments: A MagnetoCardioGraphy Approach
协作研究:动态现实环境中的认知工作负载分类:心磁图方法
- 批准号:
2320490 - 财政年份:2023
- 资助金额:
$ 52.77万 - 项目类别:
Standard Grant
Magneto-Inductive Waveguides: Interconnecting the Next Generation of Wearables and Implants
磁感应波导:互连下一代可穿戴设备和植入物
- 批准号:
2053318 - 财政年份:2021
- 资助金额:
$ 52.77万 - 项目类别:
Standard Grant
EAGER: A Magneto-Inductive Framework for Seamless Monitoring of Joint Kinematics
EAGER:用于无缝监测关节运动学的磁感应框架
- 批准号:
1842531 - 财政年份:2018
- 资助金额:
$ 52.77万 - 项目类别:
Standard Grant
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