We demonstrate a contact-lens (CL) based mobile sensing system which can be used to measure protein levels in human tear. By using a cost-effective mobile-phone-based well-plate reader and a fluorescent assay, we quantify lysozyme nonspecifically bound to CLs. We monitored the lysozyme levels of 9 healthy volunteers to establish individual baselines, and then compared these measurements to participants who had been diagnosed with Dry Eye Disease (N=6), observing a statistically significant difference in their means. Due to its non-invasive and simple operation, this method could be used for tear-based sensing and health monitoring applications in point-of-care settings and at home.
Methods of detection for key biomarkers in bodily fluids that are specific, low-cost, and non-invasive are in high demand for various biomedical applications. Specifically, field-portable and cost-effective devices which can enable these measurements to be made at home or in the field are crucial for practical and widespread use of these technologies. Plasmonic sensors form an emerging bio-sensor platform that responds to the specific adsorption of bio-molecules via a spectral change in transmission or reflection mode of operation. However, to read and quantify their spectral response, expensive and bulky optics such as broad-band light sources and high resolution spectrometers are typically employed, severely limiting their potential applications in resource-limited settings. In an effort to build low-cost and compact plasmonic readers, we have developed a computational sensing framework that uses machine learning to statistically differentiate the sensor’s spectral response from fabrication related variability and other noise factors, and select the optimal illumination bands for the lowest-possible read-out error. To validate this framework we constructed a low-cost and field-portable plasmonic reader around the optimal illumination bands selected for different plasmonic nano-hole array designs. We then validated the superior performance of our computational reader by measuring a large number of independently fabricated flexible plasmonic sensors made using scalable, nano-imprint lithography methods without the use of a clean room. Additionally, these structures can subsequently be transfer-printed onto disposable, wearable platforms where they can be chemically modified to specifically and sensitively capture target biomarkers in bio-fluids e.g., tear or sweat, enabling new applications in point-of-care diagnostics.
Development of portable and cost-effective optical imaging devices is essential for quantification of molecular bioassays at the point of care (POC). Mobile phone-based microscopy tools have shown great potential as biomedical reader platforms due to their small size, large distribution volume, and constantly improving optical properties. However, the optical detection sensitivity remains a challenge to further improve the diagnostic capabilities of microscopy and sensing devices based on mobile-phones. Here, we demonstrate a simple strategy to enhance the signal intensity of a smartphone fluorescence microscope by approximately an order of magnitude using surface-enhanced fluorescence (SEF) created by a thin silver film. This plasmonics-enhanced smartphone microscopy platform relies on an opto-mechanical attachment based on the Kretschmann configuration, where the sample is placed on a silver-coated glass coverslip and excited by a laser diode from the backside through a glass hemisphere. The fluorescence enhancement effect was systematically optimized by tuning the metal film thickness, spacer distance, excitation angle, and polarization, and experimentally validated by comparison to theoretical simulations. With this mobile device, single fluorescent beads as small as 50 nm and individual quantum dots (ca. 20 nm dia.) were detected. We further quantified the sensitivity limit of this mobile platform to be around 80 fluorophores per diffraction-limited spot by imaging DNA origami based brightness standards labeled with different numbers of fluorophores. We believe that this SEF-based mobile microscopy platform opens up various new opportunities for POC diagnostics and sensing applications in resource-limited-settings.