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Descripción
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| 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. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Sensors-Basel |
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ISSN
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1424-8220 |
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Factor de impacto JCR
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2,245 |
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Información de impacto
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Datos JCR del año 2014 |
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Volumen
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15 |
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DOI
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10.3390/s151129569 |
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Número de revista
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Desde la página
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29569 |
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Hasta la página
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29593 |
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Mes
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SIN MES |
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Ranking
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