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Immunochromatographic Diagnostic Test Analysis Using Google Glass
Author(s) -
Steve Feng,
Romain Caire,
Bingen Cortazar,
Mehmet Turan,
A. Y. Wong,
Aydogan Özcan
Publication year - 2014
Publication title -
acs nano
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 5.554
H-Index - 382
eISSN - 1936-086X
pISSN - 1936-0851
DOI - 10.1021/nn500614k
Subject(s) - computer science , upload , interface (matter) , jpeg , wearable computer , the internet , computer hardware , embedded system , computer graphics (images) , artificial intelligence , image (mathematics) , operating system , bubble , maximum bubble pressure method
We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health.

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