Direct Reading of Bona Fide Barcode Assays for Diagnostics with Smartphone Apps

The desire to develop new point-of-care (POC) diagnostic tools has led to the adaptation of smartphones to tackle limitations in state-of-the-art instrumentation and centralized laboratory facilities. Today’s smartphones possess the computer-like ability to image and process data using mobile apps;...

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Bibliographic Details
Published in:Scientific reports 2015-06, Vol.5 (1), p.11727-11727, Article 11727
Main Authors: Wong, Jessica X. H., Li, Xiaochun, Liu, Frank S. F., Yu, Hua-Zhong
Format: Article
Language:English
Subjects:
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Alzheimer's disease
Automatic Data Processing
Chorionic gonadotropin
Chorionic Gonadotropin - urine
Computers, Handheld
Data processing
Female
Gonadotropins
Humanities and Social Sciences
Humans
Instrumentation
Mobile Applications
multidisciplinary
Pituitary (anterior)
Point-of-Care Systems
Pregnancy
Pregnancy Tests, Immunologic
Science
Smartphone
Smartphones
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Summary:The desire to develop new point-of-care (POC) diagnostic tools has led to the adaptation of smartphones to tackle limitations in state-of-the-art instrumentation and centralized laboratory facilities. Today’s smartphones possess the computer-like ability to image and process data using mobile apps; barcode scanners are one such type of apps. We demonstrate herein that a diagnostic assay can be performed by patterning immunoassay strips in a bona fide barcode format such that after target binding and signal enhancement, the linear barcode can be read directly with a standard smartphone app. Quantitative analysis can then be performed based on the grayscale intensities with a customized mobile app. This novel diagnostic concept has been validated for a real-world application, i.e., the detection of human chorionic gonadotropin, a pregnancy hormone. With the possibility of multiplex detection, the barcode assay protocol promises to boost POC diagnosis research by the direct adaptation of mobile devices and apps.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep11727