EAGER: Compact Field Portable Biophotonics Instrument for Real-Time Automated Analysis and Identification of Blood Cells Impact Impacted by COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:6 publications
Grant number: 2141473
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Key facts
Disease
COVID-19Start & end year
20222025Known Financial Commitments (USD)
$220,000Funder
National Science Foundation (NSF)Principal Investigator
Bahram JavidiResearch Location
United States of AmericaLead Research Institution
University of ConnecticutResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Disease pathogenesis
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
COVID-19 pandemic quickly overwhelmed the healthcare resources in even advanced economies with large scale global fatalities not seen since the Spanish Flu of 1918. This project intends to investigate the impact of the COVID-19 virus on human red blood cells using an automated low-cost, field portable bio-photonics instrument. These studies can lead to better understanding of the impacted blood cells and precise measurement of cell anomalies for potential early detection of COVID-19. Accurate, rapid, and low-cost analysis and diagnosis of COVID-19 from blood cells with a compact field portable bio-photonics instrument interfaced with mobile devices will be a substantial advance toward widespread testing, medical diagnosis, early detection, disease prevention, and relevant data collection, particularly in remote areas without access to dedicated healthcare facilities. The proposed cross disciplinary project is based on a transformative biophotonics sensing approach for real-time analysis and disease detection and offers an alternative to conventional labor- and resource- intensive bio-molecular approaches. This analysis and capability would enable medical researchers to study and gain increased understanding of the effects of COVID-19 infections on blood cells. The proposed approach may provide a fast and reliable testing mechanism with the potential for widespread deployment, which is critical in dealing with pandemics, such as COVID-19, with high rates of infection and mortality. The success of the proposed approach would allow for automated low cost, rapid and highly accurate assessment of the impact of COVID-19 on blood cells, which is not currently possible using conventional methods. The proposed research provides new capabilities and benefits including real-time sensing and diagnosis; early detection with high accuracy, specificity, and sensitivity, and low cost field portable deployment in under resourced healthcare systems for real-time monitoring of pandemics. Investigating the impact of COVID-19 on blood cells and making detailed real-time measurements of the COVID-19 induced changes and anomalies of the blood cells at sub-micron scales would provide valuable research insights to fight COVID-19 and future pandemics. The proposed approach employs computational multi-dimensional sensing and imaging at sub-micron scales to analyze morphology and motility of blood cells. Specially embedded algorithms are integrated with mobile devices to analyze opto-biological signatures of blood cells in real time to find potential clues to the impact and presence of COVID-19 for rapid (real-time) COVID analysis and detection. The measurements and analysis of the infected cells will be performed at sub-micron scale lateral resolution and nano scale longitudinal resolution. The proposed project investigates blood cells morphology and temporal motility quantitatively with high precision using high resolution self-referencing digital holographic in compact 3D-printed platforms. Multidimensional bio-optical signature data, including spatial structure, refractive index, stiffness, and dynamic temporal behavior of the blood cells will be investigated to understand the influence of COVID-19 in blood cells. The use of dedicated machine learning algorithms associated with the analysis of anomalies in blood cells due to COVID-19 are intended to produce accurate detection and analysis. 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.
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