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14 June 2023 A COVID-19 sensor that combines lens-free microscopy, an agglutination assay, and machine learning
Euan McLeod, Colin J. Potter, Yanmei Hu, Zhen Xiong, Jun Wang
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Proceedings Volume PC12541, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXIV; PC1254108 (2023) https://doi.org/10.1117/12.2664164
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States
Abstract
Rapid, cost-effective, sensitive, and point-of-care disease sensors have become highly sought since the COVID-19 pandemic. We present an approach that achieves the sensitivity of nucleic acid amplification tests in less time. It combines an agglutination assay, lensfree microscopy, and machine learning. Antibody-coated beads sandwich virus particles and agglutinate depending on the viral concentration. By identifying particularly low levels of agglutination, we achieve a 1270 copies/mL limit of detection, comparable to polymerase chain reaction tests. Readout is performed in a cost-effective and compact device. This approach can be sped up further and used to identify other diseases in the future.
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Euan McLeod, Colin J. Potter, Yanmei Hu, Zhen Xiong, and Jun Wang "A COVID-19 sensor that combines lens-free microscopy, an agglutination assay, and machine learning", Proc. SPIE PC12541, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXIV, PC1254108 (14 June 2023); https://doi.org/10.1117/12.2664164
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KEYWORDS
Machine learning
Microscopy
Sensors
Particles
Point-of-care devices
Polymers
Proteins
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