Immunochromatographic Diagnostic Test Analysis Using Google Glass

• Published in: ACS nano 2014-03, Vol.8 (3), p.3069-3079
• Main Authors: Feng, Steve, Caire, Romain, Cortazar, Bingen, Turan, Mehmet, Wong, Andrew, Ozcan, Aydogan
• Format: Article
• Language: English
• Subjects: Chromatography, Affinity - instrumentation; Diagnostic Tests, Routine - instrumentation; Equipment Design; HIV - isolation & purification; Humans; Male; Prostate-Specific Antigen - analysis; Technology; Time Factors
• ISSN: 1936-0851; 1936-086X
• DOI: 10.1021/nn500614k

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.