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Neonatal jaundice is one of the most common reasons for hospital admission in the neonatal care unit, which it is associated to significant morbidity and mortality. Neonatal jaundice, indicated with hyper bilirubin in neonatal blood, occur in 60% of >35 weeks neonatal and 80% of <35 weeks neonatal. Therefore, it is important to develop the ease method to predict the hyper bilirubin in neonatal. This study was performed to develop the easy and objective method to determine the bilirubin in neonatal based on the forehead image captured using smartphone camera. Methodology of this research including the capturing of the neonatal forehead with the calibration color chart, followed by analyzing the image using ImageJ software to extract the color intensity of the digital images. The red, green and blue (RGB) colors were then analyzed to find the best correlation between the color intensity of neonatal forehead images with the blood bilirubin concentration. The bilirubin concentration was determined using standard method performed in the hospital based on spectrophotometric method. The smartphone-based methods of neonatal forehead images showed a linear correlation (R2=0.832) between blue color intensity and blood bilirubin concentration of neonatal observed with a regression line of y= -4.954x + l60.45. This result could be used for further self-detection by the mothers of neonatal jaundice or healthcare monitoring mainly in the remote area. [ABSTRACT FROM AUTHOR]

Neonatal jaundice is one of the common clinical conditions where the bilirubin levels are above the normal condition, which needs medical attention. It is important to the early determination of neonatal jaundice, especially in a rural area with limitations of medical instruments for bilirubin determination. This research was performed to determine neonatal jaundice using a smartphone camera. The smartphone was used to capture the arm of the neonatal. The arm images were then analyzed using ImageJ software to extract the color intensity of red, green and blue (RGB). The color intensity and the blood bilirubin concentration of neonatal were analyzed to obtain the linear regression. The results showed the blue (B) color intensity had a high correlation (R2=0.8081, y= -4.968x+165.97) with blood bilirubin concentration of neonatal observed. This study showed an important aspect of the use of smartphone camera for early detection of neonatal jaundice as an alternative of the visual assessment mainly in remote area when the laboratories analysis is not immediately available. [ABSTRACT FROM AUTHOR]

A biosensor is an analytical method that uses an active biological component that is integrated with electronic equipment to determine the analyte concentration. One of the biosensor methods widely developed is colorimetric-based detection. The purpose of this research was to study the potential of the use of purple spinach (Alternanthera brasiliana) leaf extract as a urea biosensor indicator. The research was performed including the leaf extraction, characterization, and application as a urea biosensor indicator. The results showed that the optimum purple spinach leaf extraction using Ethanol-HCl 85:15 (v/v) with an absorbance of 0.802 at a maximum wavelength of 531 nm. Furthermore, the leaf extract showed high stability in acid, low temperature (<4oC) storage, and the addition of reducing agent. The purple spinach leaf as an indicator of urea biosensor showed a linear correlation between the color change and urea concentration, with the regression line of y=-0.0007x+0.6397 and R2 of 0.961. [ABSTRACT FROM AUTHOR]

The existence of urea in human’s body becomes an important biological parameter for kidney disease identification. Development of urea analysis methods are widely studied, including the using a biosensor. This study was developed a urea biosensor using immobilized urease in alginate matrix and a light dependent (LDR) as continuous color change detector. The color detection was based in the reaction of urea with urease to produce ammonia which finally identified using bromothymol blue as color indicator. The LDR, a cheap electronic component was controlled by Arduino microcontroller to monitor the color change related to urea concentration. The result showed the optimum reaction time was 4 minutes with the best linearity was obtained by red color change with urea concentration (y = 0.42x + 39.34, R² = 0.991). Furthermore, the limit of detection of this developed urea biosensor was 0.35 mM and the limit of quantification was 1.17 mM. The linear range of the urea biosensor was 1.17 mM to 42.65 mM. The immobilized urease in alginate bead could be used up to 11 times. Urea detection in blood samples showed no significant differences between the results of the clinical analysis with the results of developed urea biosensor with a correction value of 1.3. [ABSTRACT FROM AUTHOR]