Smartphone-based colorimetric sensor application for measuring biochemical material concentration

Recent advancements of smartphone-based sensing technology for diagnosis, food safety analysis, and environmental monitoring

The emergence of computationally powerful smartphones, relatively affordable high-resolution camera, drones, and robotic sensors have ushered in a new age of advanced sensible monitoring tools. The present review article investigates the burgeoning smartphone-based sensing paradigms, including surface plasmon resonance (SPR) biosensors, electrochemical biosensors, colorimetric biosensors, and other innovations for modern healthcare. Despite the significant advancements, there are still scarcity of commercially available smart biosensors and hence need to accelerate the rates of technology transfer, application, and user acceptability. The application/necessity of smartphone-based biosensors for Point of Care (POC) testing, such as prognosis, self-diagnosis, monitoring, and treatment selection, have brought remarkable innovations which eventually eliminate sample transportation, sample processing time, and result in rapid findings. Additionally, it articulates recent advances in various smartphone-based multiplexed bio sensors as affordable and portable sensing platforms for point-of-care devices, together with statistics for point-of-care health monitoring and their prospective commercial viability.

Point-of-care blood tests using a smartphone-based colorimetric analyzer for health check-up

A microscale colorimetric assay was designed and implemented for the simultaneous determination of clinical chemistry tests measuring six parameters, including glucose (GLU), total protein (TP), human serum albumin (HSA), uric acid (UA), total cholesterol (TC), and triglycerides (TGs) in plasma samples. The test kit was fabricated using chromogenic reagents, comprising specific enzymes and binding dyes. Multiple colors that appeared on the reaction well when it was exposed to each analyte were captured by a smartphone and processed by the homemade Check6 application, which was designed as a colorimetric analyzer and simultaneously generated a report that assessed test results against gender-dependent reference ranges. Six blood checkup parameters for four plasma samples were conducted within 12 min on one capture picture. The assay achieved wide working concentration ranges of 10.45-600 mg dL-1 GLU, 1.39-10.0 g dL-1 TP, 1.85-8.0 g dL-1 HSA, 0.86-40.0 mg dL-1 UA, 11.28-600 mg dL-1 TC, and 11.93-400 mg dL-1 TGs. The smartphone-based assay was accurate with recoveries of 93-108% GLU, 93-107% TP, 92-107% HSA, 93-107% UA, 92-107% TC, and 99-113% TGs. The coefficient of variation for intra-assay and inter-assay precision ranged from 3.2-5.2% GLU, 4.6-5.3% TP, 4.3-5.3% HSA, 2.8-6.6% UA, 2.7-6.5% TC, and 1.1-3.9% TGs. This assay demonstrated remarkable accuracy in quantifying the concentration-dependent color intensity of the plasma, even in the presence of other suspected interferences commonly present in serum. The results of the proposed method correlated well with results determined by the microplate spectrophotometer (R2 > 0.95). Measurement of these six clinical chemistry parameters in plasma using a microscale colorimetric test kit coupled with the Check6 smartphone application showed potential for real-time point-of-care analysis, providing cost-effective and rapid assays for health checkup testing.

Colorimetric sensing for translational applications: from colorants to mechanisms

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

Machine learning-assisted image label-free smartphone platform for rapid segmentation and robust multi-urinalysis

This study presents a groundbreaking approach for the early detection of chronic kidney disease (CKD) and other urological disorders through an image-label-free, multi-dipstick identification method, eliminating the need for complex machinery, label libraries, or preset coordinates. Our research successfully identified reaction pads on 187 multi-dipsticks, each with 11 pads, leveraging machine learning algorithms trained on human urine data. This technique aims to surpass traditional colourimetric methods and concentration-colour curve fitting, offering more robust and precise community screening and home monitoring capabilities. The developed algorithms enhance the generalizability of machine learning models by extracting primary colours and correcting urine colours on each reaction pad. This method's cost-effectiveness and portability are significant, as it requires no additional equipment beyond a standard smartphone. The system's performance rivals professional medical equipment without auxiliary lighting or flash under regular indoor light conditions, effectively managing false positives and negatives across various categories with remarkable accuracy. In a controlled experimental setting, we found that random forest algorithms, based on a Bagging strategy and applied in the HSV colour space, showed optimal results in smartphone-assisted urinalysis. This study also introduces a novel urine colour correction method, significantly improving machine learning model performance. Additionally, ISO parameters were identified as crucial factors influencing the accuracy of smartphone-based urinalysis in the absence of additional lighting or optical configurations, highlighting the potential of this technology in low-resource settings.

Progress in the design of portable colorimetric chemical sensing devices

The need for precise determination of heavy metals, anions, biomolecules, pesticides, drugs, and other substances is vital across clinical, environmental, and food safety domains. Recent years have seen significant progress in portable colorimetric chemical sensing devices, revolutionizing on-the-spot analysis. This review offers a comprehensive overview of these advancements, covering handheld colorimetry, RGB-based colorimetry, paper-based colorimetry, and wearable colorimetry devices. It explores the underlying principles, functional materials (chromophoric reagents/dyes and nanoparticles), detection mechanisms, and their applications in environmental monitoring, clinical care, and food safety. Noble metal nanoparticles (NPs) have arisen as promising substitutes in the realm of sensing materials. They display notable advantages, including heightened sensitivity, the ability to fine-tune their plasmonic characteristics for improved selectivity, and the capacity to induce visible color changes, and simplifying detection. Integration of NPs fabricated paper device with smartphones and wearables facilitates reagent-free, cost-effective, and portable colorimetric sensing, enabling real-time analysis and remote monitoring.

Analysis of Biotinidase Activity in Serum by Digital Imaging Colorimetry Detection

Biotinidase deficiency (BD) is an autosomal recessive inherited disorder of biotin recycling that leads to neurological and cutaneous consequences if left untreated. The clinical features of BD can be ameliorated or prevented by the administration of pharmacological doses of the vitamin biotin. Since it is a treatable disorder, BD is included in the newborn screening program in Türkiye as in many other countries. Therefore, monitoring of biotinidase enzyme activity (BEA) is of vital importance, especially for patients. The aim of this study was to develop a simple and reliable colorimetric method based on digital imaging for the analysis of BEA in serum samples. To determine the optimum distance and LED light source in the analyzer box that we fabricated in the laboratory, images of the solutions in a 96-well microplate were taken with a mobile phone camera, and each color space was examined. The most reliable relationship was between blank subtracted intensities of green channel and analyte concentrations, which was in the range of 35-400 ng/mL p-aminobenzoic acid (r2 = 0.999). The limit of detection and limit of quantification were 11 and 35 ng/mL, respectively. The proposed method was successfully applied to serum samples of 60 patients with BD and 60 healthy controls. We claim that the method can be easily performed for determination of BEA anywhere without needing expensive instruments.

Development and Evaluation of a Low-Cost Triglyceride Quantification Enzymatic Biosensor Using an Arduino-Based Microfluidic System

Overweight and obesity promote diabetes and heart disease onset. Triglycerides are key biomarkers for cardiovascular disease, strokes, and other health issues. Scientists have devised methods and instruments for the detection of these molecules in liquid samples. In this study, an enzymatic biosensor was developed using an Arduino-based microfluidic platform, wherein a lipolytic enzyme was immobilized on an ethylene-vinyl acetate polymer through physical adsorption. This low-cost optical biosensor employed a spectrophotometric transducer and was assessed in liquid samples to indirectly detect triglycerides and fatty acids using p-nitrophenol as an indicator. The average triglyceride level detected in the conducted experiments was 47.727 mg/dL. The biosensor exhibited a percentage of recovery of 81.12% and a variation coefficient of 0.791%. Furthermore, the biosensor demonstrated the ability to detect triglyceride levels without the need for sample dilution, ranging from 7.6741 mg/dL to 58.835 mg/dL. This study successfully developed an efficient and affordable enzymatic biosensor prototype for triglyceride and fatty acid detection. The lipolytic enzyme immobilization on the polymer substrate provided a stable and reproducible detection system, rendering this biosensor an exciting option for the detection of these molecules.

Smartphone-Enabled Colorimetry

A smartphone is used as a colorimeter. The performance characterization for colorimetry is presented using both the built-in camera and a clip-on dispersive grating. Certified colorimetric samples provided by Labsphere^® are considered as test samples. Color measurements directly performed utilizing the smartphone camera only are obtained using the RGB Detector app, downloaded from the Google Play Store. More precise measurements are achieved using the commercially available GoSpectro grating and related app. In both cases, to quantify the reliability and sensitivity of smartphone-based color measurements, the CIELab color difference ΔE between the certified and smartphone-measured colors is calculated and is reported in this paper. In addition, as an example of a practical application of interest for the textile industry, several samples of cloth fabrics with a palette of the most common colors are measured, and the comparison with the certified color values is presented.

A field-deployable water quality monitoring with machine learning-based smartphone colorimetry

Water quality monitoring is an increasing global concern as the pollution of water sources causes adverse effects on economic growth and human health. Traditional approaches to the detection of pollutants are time-consuming and labor-intensive due to the requirement of sophisticated equipment or laboratory settings. Therefore, portable devices featuring rapid response and easy operation are indispensable in water quality monitoring. Herein, smartphone-based colorimetric pollutant quantification is demonstrated in a machine learning (ML) framework. As a proof of concept, the presence of seven ions in water was analyzed using colorimetric strips. The color variation on the strip indicators was captured under eight lighting conditions with five smartphones, providing robustness against the illumination variation and camera optics for ML classifiers. Color and texture features were extracted from the images to train the classifiers. Among the twenty-three classifiers, K-Nearest Neighbors exhibits the best classification performance, leading to the integration with our custom-designed Android application called Hydro Sens. The proposed approach was also tested with real samples taken from local water sources. The results prove that incorporating color strips with ML with a smartphone application can be used for water quality monitoring, which offers promising alternatives for sophisticated equipment that is especially applicable in resource-limited settings.

Smartphone-Based Multiplexed Biosensing Tools for Health Monitoring

Many emerging technologies have the potential to improve health care by providing more personalized approaches or early diagnostic methods. In this review, we cover smartphone-based multiplexed sensors as affordable and portable sensing platforms for point-of-care devices. Multiplexing has been gaining attention recently for clinical diagnosis considering certain diseases require analysis of complex biological networks instead of single-marker analysis. Smartphones offer tremendous possibilities for on-site detection analysis due to their portability, high accessibility, fast sample processing, and robust imaging capabilities. Straightforward digital analysis and convenient user interfaces support networked health care systems and individualized health monitoring. Detailed biomarker profiling provides fast and accurate analysis for disease diagnosis for limited sample volume collection. Here, multiplexed smartphone-based assays with optical and electrochemical components are covered. Possible wireless or wired communication actuators and portable and wearable sensing integration for various sensing applications are discussed. The crucial features and the weaknesses of these devices are critically evaluated.

A Low-Cost Paper-Based Device for the Colorimetric Quantification of Bilirubin in Serum Using Smartphone Technology

Total bilirubin values have been used as a potential marker to pre-screen and diagnose various liver-based diseases such as jaundice, bile obstruction, liver cancer, etc. A device known as KromaHealth Kit, composed of paper and an acrylic backbone, is developed to quantify total bilirubin in human serum using image processing and machine learning technology. The biochemical assays are deposited on absorbent paper pads that act as reaction zones when serum is added. A dedicated smartphone app captures images of the colorimetric changes on the pad and converts them into quantitative values of bilirubin. The range of bilirubin concentration that can be quantified using the device ranges from 0.5 mg/dl to 7.0 mg/dl. The precision, limit of detection, interference analysis, linearity, stability, and comparison with a predicate are studied in this paper in accordance with clinical and laboratory standards institute. The results indicate that the KromaHealth Kit can be used as an inexpensive alternative to conventional bilirubin testing in clinical settings. With its level of precision, ease-of-use, long shelf-life, and short turnaround time, it will prove to be invaluable in limited-resource settings.

Nano-enabled sensing of per-/poly-fluoroalkyl substances (PFAS) from aqueous systems - A review

Per-/poly-fluoroalkyl substances (PFAS) are an emerging class of environmental contaminants used as an additive across various commodity and fire-retardant products, for their unique thermo-chemical stability, and to alter their surface properties towards selective liquid repellence. These properties also make PFAS highly persistent and mobile across various environmental compartments, leading to bioaccumulation, and causing acute ecotoxicity at all trophic levels particularly to human populations, thus increasing the need for monitoring at their repositories or usage sites. In this review, current nano-enabled methods towards PFAS sensing and its monitoring in wastewater are critically discussed and benchmarked against conventional detection methods. The discussion correlates the materials' properties to the sensitivity, responsiveness, and reproducibility of the sensing performance for nano-enabled sensors in currently explored electrochemical, spectrophotometric, colorimetric, optical, fluorometric, and biochemical with limits of detection of 1.02 × 10^-6 μg/L, 2.8 μg/L, 1 μg/L, 0.13 μg/L, 6.0 × 10^-5 μg/L, and 4.141 × 10^-7 μg/L respectively. The cost-effectiveness of sensing platforms plays an important role in the on-site analysis success and upscalability of nano-enabled sensors. Environmental monitoring of PFAS is a step closer to PFAS remediation. Electrochemical and biosensing methods have proven to be the most reliable tools for future PFAS sensing endeavors with very promising detection limits in an aqueous matrix, short detection times, and ease of fabrication.

Highly sensitive and quantitative biodetection with lipid-polymer hybrid nanoparticles having organic room-temperature phosphorescence

A versatile organic room-temperature phosphorescence (RTP)-based "turn on" biosensor platform has been devised with high sensitivity by combining oxygen-sensitive lipid-polymer hybrid RTP nanoparticles with a signal-amplifying enzymatic oxygen scavenging reaction in aqueous solutions. When integrated with a sandwich-DNA hybridization assay on 96-well plates, our phosphorimetric sensor demonstrates sequence-specific detection of a cell-free cancer biomarker, a TP53 gene fragment, with a sub-picomolar (0.5 p.m.) detection limit. This assay is compatible with detecting cell-free nucleic acids in human urine samples. Simply by re-programming the detection probe, our unique methodology can be adapted to a broad range of biosensor applications for biomarkers of great clinical importance but difficult to detect due to their low abundance in vivo.

A Smartphone Optical Device for Point-of-Care Testing of Glucose and Cholesterol Using Ag NPs/UiO-66-NH2-Based Ratiometric Fluorescent Probe

Point-of-care testing (POCT) with the advantages of simplicity, rapidity, portability, and low-cost is of great importance to improve healthcare, especially in resource-limited settings and home healthcare settings. Moreover, it is a great challenge to quantitative POCT of multiplexed biomarkers within a single accessible assay but provides enhanced diagnostic accuracy and improved diagnostic efficiency. Herein, a smartphone optical device has been designed for POCT of glucose and cholesterol in metabolic syndrome patients using a ratiometric fluorescent sensor. The sensing system of Ag NPs/UiO-66-NH₂ and o-phenylenediamine presents a dual-emission response to H₂O₂ (the main product of glucose and cholesterol catalyzed by glucose oxidase and cholesterol oxidase) on account of the inner filter effect, resulting in an increase in the response of the fluorescence intensity ratio (F_555 nm/F_425 nm) accompanied by a distinguishable color transition from blue to yellow green. After compositing probes with a flexible substrate, the obtained test strip can be integrated with a smartphone-based portable platform to read RGB values for accurate testing of glucose and cholesterol with both detection limits of 10 μmol L^-1, which are hundreds of times lower than their concentrations in human serum. With the advantages of low-cost, ease of operation, and broad adaptability, this smartphone optical device holds great potential for portable detection of numerous targets in personalized healthcare and clinical diagnosis.