title: Automated Low-Cost Smartphone-Based Lateral Flow Saliva Test Reader for Drugs-of-Abuse Detection.
abstract: 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.
authors.affiliation: Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain. adrian.carrio@upm.es.
authors.forename: Adrian
authors.initials: A
authors.lastname: Carrio
authors.affiliation: Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain. carlos.sampedro@upm.es.
authors.forename: Carlos
authors.initials: C
authors.lastname: Sampedro
authors.affiliation: Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain. jl.sanchez@upm.es.
authors.forename: Jose Luis
authors.initials: JL
authors.lastname: Sanchez-Lopez
authors.affiliation: Aplitest Health Solutions, Paseo de la Castellana 164, Madrid 28046, Spain. mp@aplitest.com.
authors.forename: Miguel
authors.initials: M
authors.lastname: Pimienta
authors.affiliation: Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain. pascual.campoy@upm.es.
authors.forename: Pascual
authors.initials: P
authors.lastname: Campoy
mesh_terms: D003124:Colorimetry / Q000379:methods; D004867:Equipment Design; D006801:Humans; D013287:Illicit Drugs / Q000032:analysis*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer; D012463:Saliva / Q000737:chemistry*; D000068997:Smartphone; D015813:Substance Abuse Detection / Q000379:methods*
chemical_list: D013287:Illicit Drugs
keywords: computer vision; diagnostics; drugs-of-abuse; machine learning; neural networks; smartphone