Due to their vast availability and rapid technological advancement, smartphones have become increasingly used as a platform for development of affordable, point-of-care diagnostic devices for low-resource settings. Simultaneous detection of multiple samples can improve the effectiveness and implementation of the point-of-care detection strategies in low-resource settings, such as a primary healthcare centers, which have limited availability of skilled personnel and consumables. To address this issue, we have developed a novel optical system that allows detection of multiple analytes at the same time in a smartphone-based spectroscopic system.
Access to clinical OCT systems is currently limited to well-resourced medical centers due to their mechanical footprint, complexity and cost. Smartphone computational power and optical system quality has increased exponentially in recent years, leading to its implementation in various imaging and sensing applications. Here, we demonstrate a line-field visible-light OCT system that utilizes the native camera of a commercial smartphone and a custom phone application to collect, process and visualize 2D OCT cross-sectional data in real-time. We believe smartOCT can lead to significant impact in low-resource areas by making OCT devices accessible to a broader population.
Smartphones have been extensively demonstrated as a platform to improve the accessibility of healthcare tools in low-resource settings. We demonstrate a novel smartphone-based optical coherence tomography system (OCT) that utilizes the native optical detection and data processing capabilities of the smartphone to perform imaging at low cost and with small system footprint. In this paper, we describe the development of an Android application for real-time display and data processing from our smartphone-integrated system.
To evaluate the effect of illumination, camera orientation, and camera distance on color consistency of different skin tones, several swatches from a Pantone SkinTone Guide deck were selected and photographed at varying distances, illuminations, and angles. The RGB values from each selected swatch from each image were converted to LAB units and compared with the converted “true” values provided by Pantone. The ability of various color references to correct different skin tones was tested by comparing color values from a subject’s forearm skin to “true” color values of the closest Pantone SkinTone swatch found by visual comparison.
Present work demonstrates the operation of a smartphone platform sensor that accurately measures mercury (Hg (II)) level concentration in water. The sensing principle of the designed sensor is based on the detection of fluorescence emission from a ternary complex containing different concentration of Hg (II) in the mixture. The designed sensor correlates the level of Hg (II) concentration in a given sample through the emission of fluorescence emission from it. Using simple optical components, a compact optical set-up has been designed which can be attached to the rear-camera of the smartphone. Using the designed smartphone sensor Hg (II)-level variation as low as 50ppb can be detected accurately and reliably. The performance of the sensor has been evaluated in presence of other interfering elements such as iron, copper, zinc and manganese and we noticed that the sensor characteristic does not perturb by the presence of such elements. It has been observed that the proposed sensor performs at par with that of a laboratory grad optical spectrometer. Owing to the involvement of low-cost components and user-friendly application that essentially converts the CMOS illumination reading into a readable form we envision that the proposed sensing technique would be useful for in-field based sensing of Hg(II) level in water largely present in industrial waste water and other environmental water bodies.
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