Detection of environmental contamination such as trace-level toxic heavy metal ions mostly relies on bulky and costly analytical instruments. However, a considerable global need exists for portable, rapid, specific, sensitive, and cost-effective detection techniques that can be used in resource-limited and field settings. Here we introduce a smart-phone-based hand-held platform that allows the quantification of mercury(II) ions in water samples with parts per billion (ppb) level of sensitivity. For this task, we created an integrated opto-mechanical attachment to the built-in camera module of a smart-phone to digitally quantify mercury concentration using a plasmonic gold nanoparticle (Au NP) and aptamer based colorimetric transmission assay that is implemented in disposable test tubes. With this smart-phone attachment that weighs <40 g, we quantified mercury(II) ion concentration in water samples by using a two-color ratiometric method employing light-emitting diodes (LEDs) at 523 and 625 nm, where a custom-developed smart application was utilized to process each acquired transmission image on the same phone to achieve a limit of detection of ∼3.5 ppb. Using this smart-phone-based detection platform, we generated a mercury contamination map by measuring water samples at over 50 locations in California (USA), taken from city tap water sources, rivers, lakes, and beaches. With its cost-effective design, field-portability, and wireless data connectivity, this sensitive and specific heavy metal detection platform running on cellphones could be rather useful for distributed sensing, tracking, and sharing of water contamination information as a function of both space and time.

We demonstrate a personalized food allergen testing platform, termed iTube, running on a cellphone that images and automatically analyses colorimetric assays performed in test tubes toward sensitive and specific detection of allergens in food samples. This cost-effective and compact iTube attachment, weighing approximately 40 grams, is mechanically installed on the existing camera unit of a cellphone where the test and control tubes are inserted from the side and are vertically illuminated by two separate light-emitting-diodes. The illumination light is absorbed by the allergen assay that is activated within the tubes, causing an intensity change in the acquired images by the cellphone camera. These transmission images of the sample and control tubes are digitally processed within1 sec using a smart application running on the same cellphone for detection and quantification of allergen contamination in food products. We evaluated the performance of this cellphone based iTube platform using different types of commercially available cookies, where the existence of peanuts was accurately quantified after a sample preparation and incubation time of ~20 min per test. This automated and cost-effective personalized food allergen testing tool running on cellphones can also permit uploading of test results to secure servers to create personal and/or public spatio-temporal allergen maps, which can be useful for public health in various settings.

We demonstrate a digital sensing platform, termed Albumin Tester, running on a smart-phone that images and automatically analyses fluorescent assays confined within disposable test tubes for sensitive and specific detection of albumin in urine. This light-weight and compact Albumin Tester attachment, weighing approximately 148 grams, is mechanically installed on the existing camera unit of a smart-phone, where test and control tubes are inserted from the side and are excited by a battery powered laser diode. This excitation beam, after probing the sample of interest located within the test tube, interacts with the control tube, and the resulting fluorescent emission is collected perpendicular to the direction of the excitation, where the cellphone camera captures the images of the fluorescent tubes through the use of an external plastic lens that is inserted between the sample and the camera lens. The acquired fluorescent images of the sample and control tubes are digitally processed within one second through an Android application running on the same cellphone for quantification of albumin concentration in urine specimen of interest. Using a simple sample preparation approach which takes ~ 5 minutes per test (including the incubation time), we experimentally confirmed the detection limit of our sensing platform as 5–10 μg/mL (which is more than 3 times lower than clinically accepted normal range) in buffer as well as urine samples. This automated albumin testing tool running on a smart-phone could be useful for early diagnosis of kidney disease or for monitoring of chronic patients, especially those suffering from diabetes, hypertension, and/or cardiovascular diseases.

We demonstrate a cellphone based contact microscopy platform, termed Contact Scope, which can image highly dense or connected samples in transmission mode. Weighing approximately 76 grams, this portable and compact microscope is installed on the existing camera unit of a cellphone using an opto-mechanical add-on, where planar samples of interest are placed in contact with the top facet of a tapered fiber-optic array. This glass-based tapered fiber array has ∼9 fold higher density of fiber optic cables on its top facet compared to the bottom one and is illuminated by an incoherent light source, e.g., a simple light-emitting-diode (LED). The transmitted light pattern through the object is then sampled by this array of fiber optic cables, delivering a transmission image of the sample onto the other side of the taper, with ∼3× magnification in each direction. This magnified image of the object, located at the bottom facet of the fiber array, is then projected onto the CMOS image sensor of the cellphone using two lenses. While keeping the sample and the cellphone camera at a fixed position, the fiber-optic array is then manually rotated with discrete angular increments of e.g., 1-2 degrees. At each angular position of the fiber-optic array, contact images are captured using the cellphone camera, creating a sequence of transmission images for the same sample. These multi-frame images are digitally fused together based on a shift-and-add algorithm through a custom-developed Android application running on the smart-phone, providing the final microscopic image of the sample, visualized through the screen of the phone. This final computation step improves the resolution and also gets rid of spatial artefacts that arise due to non-uniform sampling of the transmission intensity at the fiber optic array surface. We validated the performance of this cellphone based Contact Scope by imaging resolution test charts and blood smears.