NSF/FDA SIR: Towards the Establishment of a Validation Framework for Wearable Motion Analysis Systems: Development and Evaluation of an Open-Design Sync Platform

NSF/FDA SIR：建立可穿戴运动分析系统的验证框架：开放式设计同步平台的开发和评估

• 批准号: 2229538
• 负责人: Damiano Zanotto
• 金额: $ 20万
• 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: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229538&HistoricalAwards=false
• 关键词: NSF; FDA; SIR; Towards; Establishment

Consumer-grade wearable sensors are increasingly used in biomedical and clinical research. The ability to “measure what it is supposed to measured”, is a basic requirement for any sensor used in research. Conventional validation procedures involve comparing the outputs of a wearable device with those of gold-standard laboratory equipment. For devices designed to measure human motion, this process requires millisecond-level alignment of the data measured by the two systems. As a first step toward the development of a standardized validation framework for wearable devices, this two-year NSF/FDA Scholar-in-Residence project will establish novel data-driven method to enable accurate time alignment between consumer-grade wearable sensors and stationary laboratory equipment. The models will be implemented in an open-source, affordable hardware/software Sync Platform, whose design will be disseminated for use and further development by the research community through an open repository. The project will contribute new educational materials for the PI’s graduate-level course on wearable technologies and provide a unique training opportunity for a graduate research assistant, who will learn about regulatory science by working in the collaborating FDA laboratory for part of the project.The project seeks to address the current lack of standardized validation approaches for wearable sensors used in clinical and biomedical research to quantify human motion in controlled and natural settings. The team at Stevens Institute of Technology will develop the Sync Platform consisting of a Sync Module (hardware) and a companion Sync App (mobile application) featuring novel probabilistic and learning-based data-driven delay compensation models (D3CMs) to enable accurate on-line time alignment between wearable sensors and stationary laboratory equipment. In collaboration with researchers at the FDA Center for Devices and Radiological Health (CDRH), the team will jointly evaluate the usability of the Sync Platform and its reliability under different levels of electromagnetic interference with a representative set of wearable sensors. The project will advance the state of the art on wearable technologies and biomedical research, by addressing the challenging problem of precisely synchronizing data streams from consumer-grade wearables and stationary reference instrumentation, thereby providing the foundations for the development of a standardized procedure to characterize validity and reliability of wearable devices with enhanced rigor and granularity. The methods developed in the project will also serve the broad research community by providing a tool to enable the precise alignment of data streams from heterogenous wired and wireless devices designed to capture human motion. Ultimately, these methods will promote understanding of the validity and reliability landscape afforded by commercially available wearables and assist in the design of future clinical and biomedical studies.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.

消费级可穿戴传感器越来越多地用于生物医学和临床研究。“测量它应该测量的东西”的能力是研究中使用的任何传感器的基本要求。传统的验证程序涉及将可穿戴设备的输出与黄金标准实验室设备的输出进行比较。对于用于测量人体运动的设备，这一过程需要两个系统测量的数据达到毫秒级的对齐。作为可穿戴设备标准化验证框架开发的第一步，这个为期两年的NSF/FDA驻校学者项目将建立一种新的数据驱动方法，以实现消费级可穿戴传感器和固定实验室设备之间的准确时间对齐。这些模型将在一个开源的、负担得起的硬件/软件同步平台上实施，其设计将通过一个开放的储存库传播，供研究界使用和进一步开发。该项目将为PI的可穿戴技术研究生课程提供新的教育材料，并为研究生研究助理提供独特的培训机会，该项目旨在解决目前临床和生物医学研究中用于量化人体健康的可穿戴传感器缺乏标准化验证方法的问题。在受控和自然的环境中运动。史蒂文斯理工学院的团队将开发同步平台，该平台由同步模块（硬件）和配套的同步应用程序（移动的应用程序）组成，具有新颖的概率和基于学习的数据驱动延迟补偿模型（D3 CM），以实现可穿戴传感器和固定实验室设备之间的准确在线时间对齐。该团队将与FDA器械和放射健康中心（CDRH）的研究人员合作，共同评估Sync平台的可用性及其在不同电磁干扰水平下的可靠性，并使用一组具有代表性的可穿戴传感器。该项目将通过解决消费级可穿戴设备和固定参考仪器精确同步数据流的挑战性问题，推进可穿戴技术和生物医学研究的最新发展，从而为开发标准化程序提供基础，以增强严谨性和粒度来表征可穿戴设备的有效性和可靠性。该项目开发的方法还将为广泛的研究界提供服务，提供一种工具，使来自旨在捕捉人体运动的异构有线和无线设备的数据流能够精确对齐。最终，这些方法将促进对商用可穿戴设备的有效性和可靠性的理解，并有助于设计未来的临床和生物医学研究。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。