Point-of-care colorimetric analysis through smartphone video

Abstract

Point-of-care (POC) tests often rely on smartphone image methods for colorimetric analysis, but the results of such methods are frequently difficult to reproduce or standardize. The problem is aggravated by unpredictable image capture conditions, which pose a significant challenge when low limits of detection (LOD) are needed. Application-specific smartphone attachments are often used to standardize imaging conditions, but there has recently been an interest in equipment-free POC colorimetric analysis. Improved output metrics and preprocessing methods have been developed, but equipment-free imaging often has a high LOD and is inappropriate for quantitative tasks. Additional work is necessary to replace external smartphone attachments with algorithms. Towards this end, we have developed a video processing method that synthesizes many images into a single output metric. We use image features to select the best inputs from a large set of video frames and demonstrate that the resulting output values have a stronger correlation with laboratory methods and a lower standard error. The developed algorithm only requires 20 seconds of video and can easily be integrated with existing processing methods. We apply our algorithm to the NS1-based sandwich ELISA for Zika detection and show that the LOD is two times lower when our video-based method is used.

Development of a Flow-Free Automated Colorimetric Detection Assay Integrated with Smartphone for Zika NS1

“…We used smartphone captured video and an in-house-developed desktop application to calculate the color development by TMB. Video capture instead of a single-picture capture provides the flexibility of choosing a large set of images taken over a period of time [26]. In this study, video capture plays an important role as there was no stopping solution after the TMB reaction.…”

“…After the completion of beads' movement and color development, the color was changing until saturation. Since saturation can measure the intensity of the color, it is a suitable measure for concentration-dependent colorimetric assays, and it has been reported previously [26,27]. Saturation represents the amount of intensity of color in an image and can be represented from 0 to 255 in binary scale.…”

Development of a flow-free magnetic actuation platform for an automated microfluidic ELISA

“…Using colorimetric smart phone-based detection, the end-user can be easily enabled to become a self-tester and diagnose potential illness in POC situations. 24,25 This platform has the potential to be adapted to a multitude of potential pathogens or physiological ailments detected previously through ordinary ELISA testing. Thus, the developed automated microuidic-ELISA has potential to be considered for POC disease testing and future adaptability for the next generation biosecurity measures, preventative POC diagnostics in disease epidemics, and for routine clinical monitoring at the patient's bedside.…”

“…10,15,16 Therefore, new POC diagnostics for deployable and decentralized testing are needed to help quickly diagnose and break the disease chain cycle. 17 Such challenges are met by miniaturization of the current diagnostic standards, adapting newer tools such as microuidics to establish assays, [18][19][20][21][22][23] and leveraging widespread technology such as smartphones [24][25][26][27] to potentially bridge gaps in global health, and to provide powerful epidemiological tools. [28][29][30][31][32] Previously, magnetic bead-based microuidic-ELISA systems were implemented for POC detection of M. tuberculosis 33 and for counting human CD4 + cells 34 which are commonly monitored in routine HIV/AIDS testing to help assess patient immune health.…”

A review of smartphone point‐of‐care adapter design

“…It is evident that smartphones will dominate the POC field, enabling an easy-to-use mobile application that can perform complicated laboratory tests without the need for very deep knowledge about the instrumentation and the complicated test procedures used by specialists in a large laboratory environment. 13 Recent innovations verified that smartphone-based applications are very promising demonstrating precise measurements, [14][15][16][17][18] a low limit of detection (LOD), [19][20][21][22][23] a wide dynamic range, [24][25][26][27] low power consumption, easy-to-use smart applications, a low coefficient of variation (CV%), a high regression coefficient (R 2 ), high specificity, reliable sensitivity, rapid testing, cost-effective adapter designs, and high selectivity. [28][29][30][31][32] These innovations include the major parts of POC applications, such as surgical treatment application (Section 3.2), surgical diagnosis (Section 3.1), ophthalmic applications (Section 3.3), biochemical applications (Section 3.4), [33][34][35] environmental monitoring applications, [36][37][38][39][40][41][42] biomedical applications, [43][44][45] electrochemical applications (Section 3.5), colorimetric applications, [46][47][48][49] imaging applications, [50][51]…”