• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.1
• /
• pp.13-23
• /
• 2015

Recently, a few image-processing based mobile urine testers have actively been studied since the urine-analysis result can be available to the user in real time immediately after the test is done. However, the accuracy of test result can be severely degraded due to variable illumination environments and a variety of manners to capture the image with a camera embedded in the smartphone according to different users. This paper proposes the Check4Urine system, a novel smartphone-based portable urine-analysis tester and provides three techniques to improve such a performance degradation problem robust to various test environments and disturbances, which are the compensation algorithm to correct the varying illumination effect, an urine strip detection algorithm robust to edge loss of the object image, and the color decision algorithm based on the pre-processed reference table. Experimental results show that the proposed Check4Urine system increases the accuracy of urine-analysis by 20-50% at various test conditions, compared with the existing image-processing based mobile urine tester.

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.1059-1065
• /
• 2020

In hospitals, nurses are subjectively determining the urine status to check the kidneys and circulatory system of patients whose statuses are related to patients with kidney disease, critically ill patients, and nursing homes before and after surgery. To improve this problem, this paper proposes a urine spectrum analysis system which clusters urine test results based on a hybrid machine learning model consists of unsupervised learning and supervised learning. The proposed system clusters the spectral data using unsupervised learning in the first part, and classifies them using supervised learning in the second part. The results of the proposed urine spectrum analysis system using a mixed model are evaluated with the results of pure supervised learning. This paper is expected to provide better services than existing medical services to patients by solving the shortage of nurses, shortening of examination time, and subjective evaluation in hospitals.

• Journal of Biomedical Engineering Research
• /
• v.19 no.5
• /
• pp.477-486
• /
• 1998

In this paper, we implemented the urine analysis system capable of measuring a qualitative and semi-quantitative and assay using strip. The analysis algorithm of urine analysis was adopted a fuzzy logic-based classifiers that was robust to external error factors such as temperature and electric power noises. The spectroscopic properties of 9 pads In a strip were studied to developing the urine analysis system was designed for robustnesss and stability. The urine analysis system was consisted of hardware and software. The hardware of the urine analysis system was based on one-chip microprocessor, and Its peripherals which composed of optic modulo, tray control, preamplifier, communication with PC, thermal printer and operating status indicator. The software of the urine analysis system was composed of system program and classification program. The system program did duty fort system control, data acquisition and data analysis. The classification program was composed of fuzzy inference engine and membership function generator. The membership function generator made triangular membership functions by statical method for quality control. Resulted data was transferred through serial cable to PC. The transferred data was arranged and saved be data acquisition program coded by C+ + language. The precision of urine analysis system and the stability of fuzzy classifier were evaluated by testing the standard urine samples. Experimental results showed a good stability states and a exact classification.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.7
• /
• pp.1319-1325
• /
• 2006

Urine analysis is basic test in clinical medicine using visual examination by expert nurse. Recently, this test is measured by automatic urine analysis system. But, this system has different results by each instrument. So, a new classification algorithm is required for accurate classify and urine color collection. In this paper, a intelligent color classifier of urine analysis system was designed using neural network algorithm. The input parameters are three stimulus(RGB) after preprocessing using normalization. The fuzzy inference and neural network ware constructed for classify class according to 9 urine test items and $3{\sim}7$ classes. The experiment material to be used a standard sample of medicine. The possibility to adapt classifier designed for urine analysis system was verified as classifying measured standard samples and observing classified result. Of many test items, experimental results showed a satisfactory agreement with test results of reference system.

• Journal of Biomedical Engineering Research
• /
• v.23 no.5
• /
• pp.397-403
• /
• 2002

Urine glucose monitoring system is a self-monitoring system that display the glucose level by non-invasive measurement method. In this paper, We developed a noninvasive urine glucose monitoring system that improved defects of urine glucose measurement with a colorimeter method and invasive blood glucose measurement method. This system consist of bio-chemical sensor for urine glucose measurements, signal detecting part, digital and signal analysis part, display part and power supplying part. The developed bio-chemical sensor for the measurement of urine glucose has good reproducibility, convenience of handing and can be mass-produced with cheap price. To evaluate the performance of the developed system, We performed the evaluation of confidence about the detection of glucose level by a comparison between a standard instrument in measuring glucose level and the developed system using standard glucose solutions mixed with urine. Standard error was 2.85282 from the evaluation of confidence based on regression analysis. Also, In analysis of S.D(standard deviation) and C.V(coefficient of validation) that are important parameters to evaluate system using bio-chemical sensor, S.D was 10% which falls under clinically valid value, 15%, and C.V was under 5%. Consequently from the above results, compared to blood glucose measurement, the system performance is satisfactory.

• Journal of Biomedical Engineering Research
• /
• v.24 no.3
• /
• pp.183-192
• /
• 2003

A transformation methode of the chromaticity coordinates was proposed to calibrate the measured data obtained by a urine analysis system which implemented in our previous study. Generally. the reacted color of a reagent strip by urine analysis system often exhibit the color distortions due to nonlinear characteristics of the various devices that is the optic module mechanism. hardware, and surround circumstance. A color correction method for minimizing the color distortion play a few role in maintaining high accuracy and reproduction of the urine analysis system. In this work, we used the compensation method such as the shading correction, the characteristic curve extraction of RGB color by means of third order spline interpolation, and linear transformation using a reference color. In addition, 1931 CIE XYZ color space was used to compensate the color of the measured data by a standard reference system as colorimeter. A compensation matrix was obtained so that the output values of the urine analysis system is nearly equal to that of a standard reference system for identical color sample. Color correction obtained by a urine analysis system which implemented in our previous study exhibited a good color accuracy when it was compared with the reference data. Observed result from an experiments on ten items or a urinalysis strip that color difference or between two urine analysis system was 1.28.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.10
• /
• pp.1394-1397
• /
• 2020

The urine test used as a basic test method of in vitro diagnosis for health care has been used for a long time to be simple and convenient. The urine test method is using a color that appears depending on the change in the ion concentration that reacts over time buried in the standard color test paper(Strips) with a urine sample applied to some reaction reagents. In this paper, it was proposed a neural network algorithm to obtain a suitable and reproducibility and accuracy classifier suitable for the urine analysis system. The experimental results were compared with the visual colorimetric analysis, and the neural network algorithm showed better results.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.14-18
• /
• 1997

In this paper, we suggested and made a classifier or qualitative and quantitative analysis in urine analysis system. Input variable number and fuzzy membership function was made from determination of standard sample, and the fuzzy rules were determined by the analysis of spectroscopic properties of pads in strip. Fuzzy classifier used in urine analysis system was evaluated or the standard samples in each items and degrees. Negative and positive response of urine test was classified in good property, but detail classification or quantitative analysis had 8% maximum error in each items. If fuzzy membership unction and generation of rule are supplemented, suggested fuzzy classifier can be applied to the clinical test.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.05
• /
• pp.303-308
• /
• 1997

In this paper, we analyzed the spectroscopic properties of strip to analyzer urine qualitatively & quantitatively and make urine analyzer system stable by spectroscopy, and research the property of preamplifier unit. The analysis of spectroscopic properties of 10 pads in the strip is used for determine the wave length of light source of optic detector unit and used for basic materials which are necessary that we develop the algorithm analyzing the density grade of pad accurately. We make preamplifier unit by using the current to frequency method to measure the distribution of pad color. We implemented urine analyzer system. This system's hardware is composed of measuring unit for detect of distribution density of strip pad, main processing unit, communication unit, interface device, thermal printer, and indicator. The software consists of the program which manage the argument of test, proportion initial value of urine analyzer and calibrate analyzed result.

• Journal of Biomedical Engineering Research
• /
• v.24 no.3
• /
• pp.193-201
• /
• 2003

In this paper, a classifier of urine analysis system was designed using preprocessing and fuzzy algorithm. Preprocessing were processed by normalizing data of strip using calibration curve composed of achromatic colors value and by calculating three stimulus. FUZZY classifier capable of analyzing a qualitative concentration of test items was composed of fuzzifier by gaussian shaped membership function, inference of MIN method, and defuzzifier of centroid method through verification by measuring standard solution and by classifying concentration classes. After tuning membership function according to relating standard solution with urinalysis sample, the possibility to adapt classifier designed for urine analysis system near a bed was verified as classifying measured urinalysis samples and observing classified result. Of all test items, experimental results showed a satisfactory agreement with test results of reference system.