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Sensors 2015, 15(11), 29569-29593; doi:10.3390/s151129569

Automated Low-Cost Smartphone-Based Lateral Flow Saliva Test Reader for Drugs-of-Abuse Detection

Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain
Aplitest Health Solutions, Paseo de la Castellana 164, Madrid 28046, Spain
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 31 August 2015 / Revised: 10 November 2015 / Accepted: 16 November 2015 / Published: 24 November 2015
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2015)
View Full-Text   |   Download PDF [5228 KB, uploaded 24 November 2015]   |  


Lateral flow assay tests are nowadays becoming powerful, low-cost diagnostic tools. Obtaining a result is usually subject to visual interpretation of colored areas on the test by a human operator, introducing subjectivity and the possibility of errors in the extraction of the results. While automated test readers providing a result-consistent solution are widely available, they usually lack portability. In this paper, we present a smartphone-based automated reader for drug-of-abuse lateral flow assay tests, consisting of an inexpensive light box and a smartphone device. Test images captured with the smartphone camera are processed in the device using computer vision and machine learning techniques to perform automatic extraction of the results. A deep validation of the system has been carried out showing the high accuracy of the system. The proposed approach, applicable to any line-based or color-based lateral flow test in the market, effectively reduces the manufacturing costs of the reader and makes it portable and massively available while providing accurate, reliable results. View Full-Text
Keywords: smartphone; drugs-of-abuse; diagnostics; computer vision; machine learning; neural networks smartphone; drugs-of-abuse; diagnostics; computer vision; machine learning; neural networks

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Carrio, A.; Sampedro, C.; Sanchez-Lopez, J.L.; Pimienta, M.; Campoy, P. Automated Low-Cost Smartphone-Based Lateral Flow Saliva Test Reader for Drugs-of-Abuse Detection. Sensors 2015, 15, 29569-29593.

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