CSR: EAGER: A Wearable Body Motion Sensing Platform Using Conductive Stretchable Fabric
CSR: EAGER: A Wearable Body Motion Sensing Platform Using Conductive Stretchable Fabric
批准号:
1841129
负责人:
Gang Zhou
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2020-09-30
中文摘要
该项目旨在开发一种可穿戴平台,能够生成人体骨骼的三维(3D)模型并跟踪其运动。存在使用深度相机和特殊图像处理软件来模拟人类骨骼运动的技术,微软Kinect就是一个众所周知的例子。然而,使用固定摄像头的技术需要在固定位置部署摄像头设备,以便感知人体运动。虽然这可能适用于室内固定场景,但对于室外无处不在的场景则不可行。相反,这个项目的可穿戴平台适用于这两种情况。这款可穿戴平台采用了导电性可伸缩面料,穿着舒适。为了使用可穿戴平台估计3D身体运动,需要将身体骨骼的模型与骨骼上主要关节的弯曲角度进行融合。该项目利用织物的导电电阻变化来推断织物覆盖的身体关节的用户依赖的弯曲角度。此外,针对该平台开发了一种3D运动估计方法,根据人体运动学约束优化运动估计结果。该可穿戴平台长期穿戴舒适,能够提供高运动感知精度,将极大地增强当前医疗、体育和户外娱乐的实践。老年居民和当地退休社区的福利将通过与老龄和老年健康卓越中心的合作提供。这项研究将整合到三门本科和研究生课程中。开放参观将为不同的少数民族学生和高中生提供实践机会。该项目的数据包括人类受试者数据、实验结果、软件代码和课程材料。数据收集和管理将在威廉和玛丽保护人类受试者委员会的监督下进行。数据将安全地存储在电脑上,并在William;Mary进行定期备份。项目网站为http://gzhou.blogs.wm.edu/nsf-eager-18/,项目Web服务器由William&Mary负责维护和实现。数据将在获奖期后至少保存三年。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to develop a wearable platform that enables the generation of a three dimensional (3D) model of the human skeleton and tracking its motion. There exist techniques that use depth cameras and special image processing software to model motion of the human skeleton, and Microsoft Kinect is a well-known example. However, the techniques using fixed cameras need to deploy camera devices at fixed locations in order to sense human motions. While this may be suitable for indoor fixed scenarios, it is not feasible for outdoor ubiquitous scenarios. Instead, the wearable platform from this project works for both scenarios. This wearable platform is designed using a conductive stretchable fabric that is comfortable to wear. To estimate 3D body motions using the wearable platform, the model of the body skeleton needs to be fused with the bend angles of major joints on the skeleton. This project exploits the fabric's conductive resistance change to infer user dependent bend angles of body joints that the fabric covers. Furthermore, a 3D motion estimation method is developed for the platform that optimizes motion estimation results with body kinematics constraints.Being comfortable for long-term wear and able to provide high motion sensing accuracy, this wearable platform will largely enhance the current practice of healthcare, sports, and outdoor entertainment. Benefits to senior residents and local retirement communities will be delivered through collaboration with the Center for Excellence in Aging and Geriatric Health. The research will be integrated into three undergraduate and graduate courses. Open houses will provide hands-on opportunities to a diverse group of minority students and high school students.Data from this project includes human-subjects data, experiment results, software code, and curriculum materials. Data collection and management will be under the supervision of the Protection of Human Subjects Committee at William & Mary. Data will be stored securely on computers and regularly backed-up at William & Mary. The project web site is http://gzhou.blogs.wm.edu/nsf-eager-18/ , and the project web server is maintained and achieved by William & Mary. Data will be preserved for at least three years beyond the award period.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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1016/j.smhl.2020.100143
发表时间:
2020-11
期刊:
Smart Health
影响因子:
--
作者:
[Minglong Sun;Amanda Watson;Gang Zhou]
通讯作者:
Minglong Sun;Amanda Watson;Gang Zhou
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