Dataset Information

GryphSens: A Smartphone-Based Portable Diagnostic Reader for the Rapid Detection of Progesterone in Milk.

ABSTRACT: Enzyme-linked immunosorbent assay (ELISA) is a popular assay technique for the detection and quantification of various biological substances due its high sensitivity and specificity. More often, it requires large and expensive laboratory instruments, which makes it difficult to conduct when the tests must be performed quickly at the point-of-care (POC). To increase portability and ease of use, we propose a portable diagnostic system based on a Raspberry Pi imaging sensor for the rapid detection of progesterone in milk samples. We designed, assembled, and tested a standalone portable diagnostic reader and validated it for progesterone detection against a standard ELISA assay using a commercial plate reader. The portable POC device yielded consistent results, regardless of differences in the cameras and flashlights between various smartphone devices. An Android application was built to provide front-end access to users, control the diagnostic reader, and display and store the progesterone measurement on the smartphone. The diagnostic reader takes images of the samples, reads the pixel values, processes the results, and presents the results on the handheld device. The proposed POC reader can perform to superior levels of performance as a plate reader, while adding the desirable qualities of portability and ease of use.

SUBMITTER: Jang H

PROVIDER: S-EPMC5470469 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Publications

GryphSens: A Smartphone-Based Portable Diagnostic Reader for the Rapid Detection of Progesterone in Milk.

Jang Hyunwook H Ahmed Syed Rahin SR Neethirajan Suresh S

Sensors (Basel, Switzerland) 20170510 5

Enzyme-linked immunosorbent assay (ELISA) is a popular assay technique for the detection and quantification of various biological substances due its high sensitivity and specificity. More often, it requires large and expensive laboratory instruments, which makes it difficult to conduct when the tests must be performed quickly at the point-of-care (POC). To increase portability and ease of use, we propose a portable diagnostic system based on a Raspberry Pi imaging sensor for the rapid detection ...[more]

PMID: 28489036

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Project description:Water quality is undergoing significant deterioration due to bacteria, pollutants and other harmful particles, damaging aquatic life and lowering the quality of drinking water. It is, therefore, important to be able to rapidly and accurately measure water quality in a cost-effective manner using e.g., a turbidimeter. Turbidimeters typically use different illumination angles to measure the scattering and transmittance of light through a sample and translate these readings into a measurement based on the standard nephelometric turbidity unit (NTU). Traditional turbidimeters have high sensitivity and specificity, but they are not field-portable and require electricity to operate in field settings. Here we present a field-portable and cost effective turbidimeter that is based on a smartphone. This mobile turbidimeter contains an opto-mechanical attachment coupled to the rear camera of the smartphone, which contains two white light-emitting-diodes to illuminate the water sample, optical fibers to transmit the light collected from the sample to the camera, an external lens for image formation, and diffusers for uniform illumination of the sample. Including the smartphone, this cost-effective device weighs only ~350 g. In our mobile turbidimeter design, we combined two illumination approaches: transmittance, in which the optical fibers were placed directly below the sample cuvette at 180° with respect to the light source, and nephelometry in which the optical fibers were placed on the sides of the sample cuvette at a 90° angle with respect to the to the light source. Images of the end facets of these fiber optic cables were captured using the smart phone and processed using a custom written image processing algorithm to automatically quantify the turbidity of each sample. Using transmittance and nephelometric readings, our mobile turbidimeter achieved accurate measurements over a large dynamic range, from 0.3 NTU to 2000 NTU. The accurate performance of our smartphone-based turbidimeter was also confirmed with various water samples collected in Los Angeles (USA), bacteria spiked water samples, as well as diesel fuel contaminated water samples. Having a detection limit of ~0.3 NTU, this cost-effective smartphone-based turbidimeter can be a useful analytical tool for screening of water quality in resource limited settings.

Dataset Information

GryphSens: A Smartphone-Based Portable Diagnostic Reader for the Rapid Detection of Progesterone in Milk.

Publications

GryphSens: A Smartphone-Based Portable Diagnostic Reader for the Rapid Detection of Progesterone in Milk.

Similar Datasets

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