CAREER: Structures as Sensors: Elder Activity Level Monitoring through Structural Vibrations

职业：结构作为传感器：通过结构振动监测老年人的活动水平

• 批准号: 2026699
• 负责人: Hae Young Noh
• 金额: $ 42.06万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026699&HistoricalAwards=false
• 关键词: CAREER; Structures; Sensors; Elder; Activity

The goal of this Faculty Early Career Development Program (CAREER) project is to enable "smart buildings" that can locate and identify specific individuals, and classify their activity, based only on the vibrations of the building structure caused by footsteps. Elder care facilities aim to maintain or improve the quality of life and independence of elders while reducing costs and capacity needs for care-professionals. One key to achieving this goal is to understand the activities of each occupant. Existing solutions to monitor occupants, such as vision, acoustic, motion, and force sensors and mobile devices, have strict installation requirements. These requirements lead to intrusive and dense deployment or require active user involvements. Instead, this project is built upon sensing the vibrations created by occupants' during their walking activity. Using building vibration to monitor occupants allows non-intrusive and scalable monitoring with inexpensive vibration sensors. More generally, this research will enable smart buildings to sense, track, and predict the status of occupants in a maintainable way using "structures as sensors" and thus enable future occupant-aware applications. Similarly, the technology can locate portions of a building with slippery or unsafe footing, or detect the presence of unauthorized people in restricted areas. By tracking first responders and locating imperiled civilians, such systems will also help dispatchers to mitigate emergencies. The project includes proof-of-concept deployments in three different elder care facilities. Targeted outreach activities will highlight the capabilities of this technology at an appropriate level of detail to appeal to female middle-school students.This project uses structures themselves as activity sensors, by passively sensing footstep-induced floor vibrations, and employing advanced sparse-signal approximation in a Bayesian framework, to extract individual activity information. The specific research thrusts are: (1) extracting individual persons' footstep-induced floor vibration signal from a noisy signal mixture due to multiple human sources, by exploiting hierarchical wavelet decompositions and applying structured sparsity regularization; (2) localizing individual footsteps by dynamically fusing information from multiple frequency components and leveraging human mobility and structural vibration patterns through Bayesian updating; and (3) improving model accuracy by iteratively fusing location information and signal separation. The key novelty in these thrusts lies in fusion of signal processing methods and physical constraints to address real world challenges.

这个教师早期职业发展计划（Career）项目的目标是使“智能建筑”能够定位和识别特定的个人，并根据脚步声引起的建筑结构振动对他们的活动进行分类。老年人护理设施旨在维持或改善老年人的生活质量和独立性，同时降低护理专业人员的成本和能力需求。实现这一目标的一个关键是了解每个居住者的活动。现有的监控居住者的解决方案，如视觉、声学、运动、力传感器和移动设备，都有严格的安装要求。这些需求会导致侵入性和密集的部署，或者需要用户积极参与。相反，这个项目是建立在感知居住者在步行活动中产生的振动的基础上的。使用建筑物振动来监测居住者，可以使用廉价的振动传感器进行非侵入式和可扩展的监测。更一般地说，这项研究将使智能建筑能够使用“结构作为传感器”以一种可维护的方式感知、跟踪和预测居住者的状态，从而实现未来的居住者感知应用。同样，该技术可以定位建筑物中滑溜或不安全的部分，或者检测到禁区内未经授权的人员的存在。通过跟踪第一响应者和定位危险的平民，这种系统还将帮助调度员减轻紧急情况。该项目包括在三个不同的老年护理机构进行概念验证部署。有针对性的外展活动将在适当的细节水平上突出这项技术的能力，以吸引女中学生。该项目使用结构本身作为活动传感器，通过被动地感知脚步声引起的地板振动，并在贝叶斯框架中采用先进的稀疏信号近似，提取个体活动信息。具体研究方向为：(1)利用分层小波分解和结构化稀疏正则化技术，从多人为噪声源的混合噪声信号中提取个体脚步声诱发的地板振动信号；(2)通过贝叶斯更新，动态融合多频率分量信息，利用人的移动性和结构振动模式定位个体足迹；(3)通过位置信息和信号分离的迭代融合提高模型精度。这些研究的关键新颖之处在于融合了信号处理方法和物理约束，以应对现实世界的挑战。

项目成果

Structure- and Sampling-Adaptive Gait Balance Symmetry Estimation Using Footstep-Induced Structural Floor Vibrations

• DOI: 10.1061/(asce)em.1943-7889.0001889
• 发表时间: 2021-02-01
• 期刊: JOURNAL OF ENGINEERING MECHANICS
• 影响因子: 3.3
• 作者: Fagert, Jonathon;Mirshekari, Mostafa;Noh, Hae Young
• 通讯作者: Noh, Hae Young

Recursive Sparse Representation for Identifying Multiple Concurrent Occupants Using Floor Vibration Sensing

• DOI: 10.1145/3517229
• 发表时间: 2022-03-01
• 期刊: PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT
• 作者: Fagert, Jonathon;Mirshekari, Mostafa;Noh, Hae Young
• 通讯作者: Noh, Hae Young

Obstruction-invariant occupant localization using footstep-induced structural vibrations

• DOI: 10.1016/j.ymssp.2020.107499
• 发表时间: 2021-05-15
• 期刊: MECHANICAL SYSTEMS AND SIGNAL PROCESSING
• 影响因子: 8.4
• 作者: Mirshekari, Mostafa;Fagert, Jonathon;Noh, Hae Young
• 通讯作者: Noh, Hae Young

Clean Vibes: Hand Washing Monitoring Using Structural Vibration Sensing

• DOI: 10.1145/3511890
• 发表时间: 2022-03
• 期刊: ACM Transactions on Computing for Healthcare (HEALTH)
• 作者: Jonathon Fagert;Amelie Bonde;Sruti Srinidhi;Sarah Hamilton;Pei Zhang;Hae Young Noh

Social Distancing Compliance Monitoring for COVID-19 Recovery Through Footstep-Induced Floor Vibrations

通过脚步引起的地板振动对 COVID-19 恢复进行社交距离合规性监测

• DOI: 10.1145/3485730.3492893
• 发表时间: 2021
• 期刊: SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems
• 作者: Dong, Yiwen;Wu, Yuyan;Noh, Hae Young
• 通讯作者: Noh, Hae Young