Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader.
Sensors (Basel)
; 22(5)2022 Feb 27.
Article
in English
| MEDLINE | ID: covidwho-1715645
ABSTRACT
Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Biosensing Techniques
/
COVID-19
Type of study:
Diagnostic study
Limits:
Humans
Language:
English
Year:
2022
Document Type:
Article
Affiliation country:
S22051880
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