Accessory-free quantitative smartphone imaging of colorimetric paper-based assays.


Journal

Lab on a chip
ISSN: 1473-0189
Titre abrégé: Lab Chip
Pays: England
ID NLM: 101128948

Informations de publication

Date de publication:
07 06 2019
Historique:
pubmed: 3 5 2019
medline: 26 12 2019
entrez: 3 5 2019
Statut: ppublish

Résumé

The combination of smartphone technology and colorimetric paper-based microfluidics can enable simple, inexpensive diagnostics. However, imaging colorimetric diagnostic results via smartphones currently requires accessories to mitigate the influence of variability in surrounding lighting conditions. Here, we present an accessory-free smartphone-based colorimetric imaging method that enlists the built-in LED light source to dominate ambient lighting in combination with background and colour rescaling. This simple approach enables quantitative measurements from paper-based tests by compensating for different environmental lighting conditions and is universally applicable with respect to phone models and manufacturers. We demonstrate the method with three dominant phone makes and models in a cell counting application with a paper-based yeast detection device. The detection results are in good agreement with cell counting using automated cell counters. Eliminating the need for make/model specific accessories, this approach helps realize the potential for low-cost, broadly applicable paper-based diagnostics.

Identifiants

pubmed: 31044203
doi: 10.1039/c9lc00165d
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1991-1999

Subventions

Organisme : CIHR
Pays : Canada

Auteurs

Tian Kong (T)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca.

Jae Bem You (JB)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca.

Biao Zhang (B)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca and Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Chongqing University, Chongqing 400044, China.

Brian Nguyen (B)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca.

Farhang Tarlan (F)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca.

Keith Jarvi (K)

Department of Surgery, Division of Urology, Mount Sinai Hospital, University of Toronto, 600 University Avenue, Toronto, Ontario, M5G 1X5 Canada.

David Sinton (D)

Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario, M5S 3G8 Canada. sinton@mie.utoronto.ca.

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Classifications MeSH