Two low-cost digital camera-based platforms for quantitative creatinine analysis in urine

Debus, B.; Kirsanov, Dmitry; Yaroshenko, Irina; Sidorova, A. A.; Piven, Alena; Legin, Andrey

doi:10.1016/j.aca.2015.09.007

Cited by 41 publications

(18 citation statements)

References 38 publications

(31 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1 In the most recent years, different research groups have used image analysis as an analytical tool in several distinct areas of knowledge: in food science and technology for visual inspection of fruit 4 and for the development of a portable iPhone-DIC system for the quantification of tetracycline residues in milk; 5 in forensic applications, where the Simon presumptive color test is used in combination with a built-in digital camera on a mobile phone to detect methamphetamine; 6 and for the diagnosis of kidney failure through the ascertainment of creatinine in urine samples. 7 These tools were also used in the development of a simple, fast, and safe method to identify adulteration of cow's milk based on the building of color histograms in RGB and/or HSI scales. 8 Some authors described the use of a smartphone in a Bradford assay, a method of determining protein concentrations that is used for a variety of applications in fundamental biomedical research, utilizing a smartphone spectrometer, 9 a G-Fresnel device with the dual functionality of focusing and dispersion is used to enable miniaturization.…”

Section: Introductionmentioning

confidence: 99%

PhotoMetrix: An Application for Univariate Calibration and Principal Components Analysis Using Colorimetry on Mobile Devices

Helfer¹,

Magnus²,

Böck³

et al. 2016

Journal of the Brazilian Chemical Society

View full text Add to dashboard Cite

This article describes the development of a mobile colorimetric analysis tool. The application, called PhotoMetrix, employs the techniques of simple linear correlation for univariate analysis and principal components analysis (PCA) for multivariate exploratory analysis. The image data are captured by the main camera of the device and converted into red, green and blue (RGB) histograms. As regards the application, the iron determinations were performed in vitamin supplements (univariate module) and differentiation of banknotes was performed by PCA (multivariate module). For the iron determinations, three samples of vitamins at concentrations of 14, 40 and 50 mg of iron per tablet were tested and the results were not statistically significant (p > 0.05) compared to the reference method. The differentiation of banknotes was performed on Brazilian and Argentinean banknotes. The results showed clustering of the same types of banknotes, and through the loadings graph it was possible to observe the variables through the formation of clusters.

show abstract

Section: Introductionmentioning

confidence: 99%

PhotoMetrix: An Application for Univariate Calibration and Principal Components Analysis Using Colorimetry on Mobile Devices

Helfer¹,

Magnus²,

Böck³

et al. 2016

Journal of the Brazilian Chemical Society

View full text Add to dashboard Cite

show abstract

“…It seems that the use of colorimetric methods using a smartphone is the easiest way to detect creatinine concentrations. But this method is not very accurate at present and requires a lot of studies 23,166 . The goal of all these researches is to provide a new method for building up a small biosensor that is used by the patient remedies.…”

Section: Discussionmentioning

confidence: 99%

Trend in creatinine determining methods: Conventional methods to molecular‐based methods

Narimani

Esmaeili

Rasta

et al. 2020

Analytical Science Advances

View full text Add to dashboard Cite

Renal failure (RF) disease is ranked as one of the most prevalent diseases with severe morbidity and mortality. Early diagnosis of RF leads to subsequent control of disease to reduce the poor prognosis. The level of sera creatinine is considered as a significant biomarker for kidney biofunction, which is routinely detected by the Jaffe reaction. The normal range for creatinine in the blood may be 0.84‐1.21 mg/dL. Low accuracy, insufficient sensitivity, explosive and toxicity of picric acid, and pseudo‐interaction with nonspecific elements such as ammonium ions in the Jaffe method lead to the development of various techniques for precise detection of creatinine such as spectroscopic, electrochemical, and chromatography approaches and sensors based on enzymes, molecular imprinted polymer and nanoparticles, etc. Based on previously established results, they are trying to construct sensors with high accuracy, optimum sensitivity, acceptable linear/calibration range, and limit of detection, which are small in size and applicable by the patient him/herself (point‐of‐care testing). By comparing the results of research, a molecularly imprinted electrochemiluminescence‐based sensor with linear/calibration range of 5‐1 mM0.33emconcentration of creatinine and the detection limit of 0.5 nM has the best detectable resolution with 2 million measurable points. In this paper, we will review the recently developed methods for measuring creatinine concentration and renal biofunction.

show abstract

“…Built-in sensors, diverse applications, and constant connection through wireless data service make smartphones ideal point-of-care devices. Smartphone-based biosensing is demonstrated in different point-of-care diagnostic tests such as markers for HIV and hepatitis (Giavazzi et al 2014), ovarian cancer biomarker (Wang et al 2011), creatinine in urine samples (Debus et al 2015), or bacteria in blood (Choi et al 2016) and urine (Cho et al 2015), showing that smartphonebased point-of-care diagnostics can become a broadly applied biotechnological tool. An easy-to-use point-ofcare device with a potential commercial application is demonstrated for the quantification of cholesterol (Oncescu, Mancuso & Erickson, 2014), an alarming parameter important for preventing heart disease.…”

Section: Healthcare and Point-of-care Diagnosticsmentioning

confidence: 99%

Wireless and mobile optical chemical sensors and biosensors

Kassal

Horak

Sigurnjak

et al. 2018

Reviews in Analytical Chemistry

View full text Add to dashboard Cite

This review explores the current state-of-the-art wireless and mobile optical chemical sensors and biosensors. The review is organised into three sections, each of which investigates a major class of wireless and/or mobile optical chemical sensor: (i) optical sensors integrated with a radio transmitter/transceiver, (ii) wearable optical sensors, and (iii) smartphone camera-based sensors. In each section, the specific challenges and trade-offs surrounding the (bio)chemical sensing mechanism and material architecture, miniaturisation, integration, power requirements, readout, and sensitivity are explored with detailed examples of sensor systems from the literature. The analysis of 77 original research articles published between 2007 and 2017 reveals that healthcare and medicine, environmental monitoring, food quality, and sport and fitness are the target markets for wireless and mobile optical chemical sensor systems. In particular, the current trend for personal fitness tracking is driving research into novel colourimetric wearable sensors with smartphone readout. We conclude that despite the challenges, mobile and wearable optical chemical sensor systems are set to play a major role in the sensor Internet of Things.

show abstract

Two low-cost digital camera-based platforms for quantitative creatinine analysis in urine

Cited by 41 publications

References 38 publications

PhotoMetrix: An Application for Univariate Calibration and Principal Components Analysis Using Colorimetry on Mobile Devices

PhotoMetrix: An Application for Univariate Calibration and Principal Components Analysis Using Colorimetry on Mobile Devices

Trend in creatinine determining methods: Conventional methods to molecular‐based methods

Wireless and mobile optical chemical sensors and biosensors

Contact Info

Product

Resources

About