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There have been tremendous innovations in microfluidic clinical diagnostics to facilitate novel point-of-care testing (POCT) over the past decades. However, the automatic operation of microfluidic devices that minimize user intervention still lacks reliability and repeatability because microfluidic errors such as bubbles and incomplete filling pose a major bottleneck in commercializing the microfluidic devices for clinical testing. In this work, for the first time, various states of microfluid were recognized to control immunodiagnostics by artificial intelligence (AI) technology. The developed AI-controlled microfluidic platform was operated via an Android smartphone, along with a low-cost polymer device to effectuate enzyme-linked immunosorbent assay (ELISA). To overcome the limited machine-learning capability of smartphones, the region-of-interest (ROI) cascading and conditional activation algorithms were utilized herein. The developed microfluidic chip was incorporated with a bubble trap to remove any bubbles detected by AI, which helps in preventing false signals during immunoassay, as well as controlling the reagents' movement with an on-chip micropump and valve. Subsequently, the developed immunosensing platform was tested for conducting real ELISA using a single microplate from the 96-well to detect the Human Cardiac Troponin I (cTnI) biomarker, with a detection limit as low as 0.98 pg/mL. As a result, the developed platform can be envisaged as an AI-based revolution in microfluidics for point-of-care clinical diagnosis.

Herein, we have developed a fully automated optofluidic device to execute enzyme-linked immunosorbent assay (ELISA) using an active 96-well hybrid lab-on-a-chip (LOC) device. To automate the solution loading into the reaction zone of the device and the post-assayed signal analysis, laser irradiation-induced image whitening was utilized with a smartphone-based optical platform. Two optical phenomena were utilized in our platform to detect the liquid in the reaction chamber using a smartphone. First, by Fresnel's equation, the refraction difference between air and water resulted in the intensity change of the reflected light from the reaction chamber. Therefore, when the liquid was entering into the reaction chamber, the intensity of the reflected light was changed. Second, when the light intensity increases, the smartphone-captured image whitens out due to saturation, even when the red color light was incident. Therefore, by measuring the RGB value of the smartphone image, the intensity changes by the liquid movement in the reaction chamber were successfully monitored. Our platform showed a low detection limit of 7.81 pg/mL for the detection of the NT-proBNP human cardiac biomarker with almost a half standard deviation, compared to the manually operated LOC-based ELISA. As a fully automated LOC adopting a conventional 96-well ELISA platform, we thus concluded that the developed platform can be widely applied for point-of-care clinical tests.

In this study, an immunosensing platform by integrating a single array of conventional 96-well cartridges with low-cost polydimethylsiloxane (PDMS) pillars and thermoplastic chip was designed and developed to execute enzyme-linked immunosorbent assay (ELISA). The platform provides multiple (eight) reaction chambers for sequentially detecting multiple analytes under similar assay environments. For multiple immunoassays, the reaction chambers are consequently activated using a microvalve integrated with the sensing zones via the thermoplastic chip. Because the reaction zones are able to be selected and isolated from each other by the microvalve, multiple immunoassays can be implemented, avoiding cross-contamination. The performance of the sensing platform demonstrated its effectiveness in assaying with an optimal sample volume of 10 μL with an assay time of 10-15 min for different assay steps, which is much lower than the conventional immunoassay using 96-well plates. Thus, a low detection limit of 9.75 pg/mL is achieved using the developed platform to successfully detect the cardiac troponin I (cTnI). As a result, the cost-effectively made PDMS pillars and 96-well cartridge based hybrid immunosensing platform are widely applicable for high-throughput multiple lab-on-a-chip immunoassays.

In this work, a disposable paper-plastic hybrid microfluidic lab-on-a-chip (LOC) has been developed and successfully applied for the colorimetric measurement of urine by the smartphone-based optical platform using a "UrineAnalysis" Android app. The developed device was cost-effectively implemented as a stand-alone hybrid LOC by incorporating the paper-based conventional reagent test strip inside the plastic-based LOC microchannel. The LOC device quantitatively investigated the small volume (40 μL) of urine analytes for the colorimetric reaction of glucose, protein, pH, and red blood cell (RBC) in integration with the finger-actuating micropump. On the basis of our experiments, the conventional urine strip showed large deviation as the reaction time goes by, because dipping the strip sensor in a bottle of urine could not control the reaction volume. By integrating the strip sensor in the LOC device for urine analysis, our device significantly improves the time-dependent inconstancy of the conventional dipstick-based urine strip, and the smartphone app used for image analysis enhances the visual assessment of the test strip, which is a major user concern for the colorimetric analysis in point-of-care (POC) applications. As a result, the user-friendly LOC, which is successfully implemented in a disposable format with the smartphone-based optical platform, may be applicable as an effective tool for rapid and qualitative POC urinalysis.