We report a label-free method for detection of the SARS-CoV-2 virus in nasopharyngeal swab samples without purification steps and multiplication of the target which simplifies and expedites the analysis process. The kit consists of a textile grid on which liquid crystals (LC) are deposited and the grid is placed in a crossed polarized microscopy. The swab samples are subsequently placed on the LCs. In the presence of a particular biomolecule, the direction of LCs changes locally based on the properties of the biomolecule and forms a particular pattern. As the swab samples are not perfectly purified, image processing and machine learning techniques are employed to detect the presence of specific molecules or quantify their concentrations in the medium. The method can differentiate negative and positive COVID-19 samples with an accuracy of 96% and also differentiate COVID-19 from influenza types A and B with an accuracy of 93%. The kit is portable, simple to manufacture, convenient to operate, cost effective, rapid and sensitive. The simplicity of the specimen processing, the speed of image acquisition, and fast diagnostic operations enable the deployment of the proposed technique for performing extensive on-spot screening of COVID-19 in public places.
Keywords: COVID-19; Diagnostic; Influenza types A and B; Liquid crystals; Machine learning.
© 2022 The Authors.