Planning Grant: Engineering Research Center for the Next-generation Enterprise to Engineer Diagnostics at Low-cost for the home-Ecosystem (NEEDLE)

点击翻译按钮获取中文摘要

The health-care supply chain is fragile, as illustrated by the breakdowns in care delivery experienced during COVID-19. While advances in digital health have the potential to improve the health-services supply chain, the range of available state-of-the-art health-sensor technologies for at-home patient use is minimal and severely limited in accuracy. Moreover, these sensors are limited to a common group of measures such as body temperature, blood pressure, weight, oxygen saturation, and glucose monitoring. Therefore, the technology does not exist to provide health practitioners with sufficient, remote patient diagnostic information that reasonably approximates data obtained from traditional in-person medical visits. This grant seeks to map out a vision for an Engineering Research Center (ERC) that will produce the next generation of home-health diagnostic technologies to effectively bring the medical lab and physician to the home. Thus, the project will launch specialized workshops to explore the feasibility of an NSF ERC for the Next-generation Enterprise to Engineer Diagnostics at Low-cost for the home-Ecosystem (NEEDLE). Outcomes from the workshops will be broadly disseminated via publications and conference presentations. Finally, the involvement of a postdoctoral researcher to help coordinate activities, as well as a seed competition for student teams collaborating across three universities, provides an opportunity to train the next generation of innovators in technology development. A NEEDLE ERC could spawn the development of technologies that could significantly strengthen the health-services supply chain by directly connecting every home to the digital-health ecosystem. This ERC will focus on creating a diagnostic toolkit that will provide every home with the medical equivalent of the physical exam (e.g., inspection, palpation, and percussion) and standard lab tests (e.g., complete blood count, basic metabolic, and viral load) found at a medical facility, along with an AI-enabled data infrastructure for personalized health monitoring. The highly integrated and complex nature of the problem requires a convergence of community stakeholders, and experts in areas such as biomaterial sensors, non-invasive biological imaging, micro/nanofabrication, spectroscopy, data science, micro/nanoelectronics, and advanced signal processing. The proposed planning-grant will introduce workshops aimed at bringing these communities together to produce a needs-assessment report and a 10-year roadmap of the scientific and technological breakthroughs needed to develop home diagnostics. These activities will enable the formulation of a deployment strategy to mitigate any barriers to accessibility for developed technologies, including cost and general usability, especially for populations experiencing potential age-related cognitive decline, populations without “digital native” experience with technology, or those living in zones with inadequate Wi-Fi accessibility.This project is jointly funded by the ERC Program/EEC Division of the Engineering Directorate and the Established Program to Stimulate Competitive Research (EPSCoR).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.