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Chen X.,Fuzhou University | Chen X.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology | Du M.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2012

Traditional PCR instrument detects the temperature of reagent with contact measurement, which has several limitations such as thermal hysteresis, reagent contamination and point-measurement. Thus an infra red thermometer is applied to contactlessly measure the temperature of reagent. But infra red thermometer has the defect of relatively high measurement noise. Therefore, we propose a sequential dual Kalman filter (Seq-DKF) algorithm that uses an iterated extended Kalman filter (IEKF) and a linear Kalman filter (KF) to remove the measurement noise from infra red thermometer signals in real-time. In this algorithm, IEKF and KF are executed sequentially. The former filter rapidly identifies the parameter of heat exchange model with a small number of observations. The latter one filters the temperature signal based on the identified model. After specifying the heat exchange model and the Seq-DKF, we apply the algorithm to the PCR instrument for testing. Finally, the other three filters are employed for comparison to demonstrate the effectiveness of the Seq-DKF algorithm. Source


Li Y.,Fuzhou University | Zeng N.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology | Du M.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology
Journal of Computers | Year: 2011

Gold immunochromatographic strip assay is a rapid, simple, single-copy and on-site method. Quantitative Interpretation of the strip can provide more information than the traditional qualitative or semiquantitative strip assay. The paper aims to develop an image based assay method for quantitative determination of trace concentrations by gold immunochromatographic strip. The image of gold immunochromatographic strip is taken by CCD, and, after the proper filter and window cutting, the test line and control line is segmented by the genetic fast fuzzy c-means(FCM) clustering algorithm. In order to improve the measure property, based on Lambert-beer law, the relative reflective integral optical density(RIOD) is selected as the feature by which the interference in the test and control lines can be canceled out each other. The proposed method is applied to the quantitative detection of human chorionic gonadotropin (hCG) as a model. Firstly, the segmentation performance of the genetic fast FCM clustering algorithm is compared with threshold method and FCM clustering algorithm in terms of the peak signalto- noise ratio (PSNR). Furthermore, the comparison of the blind experiment between the proposed method and commercial quantitative instrument swp-sc1 is carried out. This method is shown to deliver a result comparable and even superior to existing techniques. © 2011 ACADEMY PUBLISHER. Source


Zeng N.,Fuzhou University | Zeng N.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology | Wang Z.,Brunel University | Li Y.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology | And 2 more authors.
IEEE Transactions on Nanotechnology | Year: 2012

In this paper, the particle filtering approach is used, together with the kernel smoothing method, to identify the state-space model for the lateral flow immunoassay through available but short time-series measurement. The lateral flow immunoassay model is viewed as a nonlinear dynamic stochastic model consisting of the equations for the biochemical reaction system as well as the measurement output. The renowned extended Kalman filter is chosen as the importance density of the particle filter for the purpose of modeling the nonlinear lateral flow immunoassay. By using the developed particle filter, both the states and parameters of the nonlinear state-space model can be identified simultaneously. The identified model is of fundamental significance for the development of lateral flow immunoassay quantification. It is shown that the proposed particle filtering approach works well for modeling the lateral flow immunoassay. © 2011 IEEE. Source


Jiang H.,Fuzhou University | Jiang H.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology | Du M.,Fuzhou University | Ke D.,Fuzhou University
Journal of Computers (Finland) | Year: 2012

alpha-fetoprotein (AFP) is a useful diagnostic marker for the detection of a great number of infantile diseases, especially for some forms of malignant tumors and liver disorders. Although there are several methods for quantitative determination of AFP, compared with these methods, the gold immunochromatographic assay (GICA)has the advantages of easy to handle, low costs, quick, no requirement for skilled technicians and most important, well suitable for point-of-care measurements. However, GICA mostly has been used for qualitative or semi-quantitative detection visually. This paper presents a rapid quantitative determination method of AFP with GICA strip based on the reflective optical detection. Under the driving of the micro-stepper motor, we can get a curve of GICA strip signal distribution. Then after segmentation of the test line and control line using fuzzy c-means clustering algorithm, the features were extracted to be as the input features of Support Vector Regression (SVR) model. SVR was used for prediction of the AFP concentration. To evaluate the reliability and accuracy of GICA for fast quantitatively determination of AFP and its clinical value, the AFP concentration of specimen was tested by GICA and chemiluminescent immunoassay analyzer, and analyzed the coincident rate and correlation of these two methods. The experiment results demonstrated that the correlation coefficient results between the two methods was 0.961. The test results showed that the SVR model yields a good result and is proved to be appropriate in quantitative determination of AFP with GICA strip. © 2012 Academy Publisher. Source


Zeng N.,Fuzhou University | Li Y.,Fuzhou University | Du M.,Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology
Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010 | Year: 2010

In this paper, a CCD-based imaging gold immunochromatographic assay system combining genetic fast FCM algorithm is developed for rapid quantitative detection of human chorionic gonadotropin(hCG). The image of gold immunochromatographic strip is taken by CCD sensor, and after using the genetic fast FCM algorithm to precisely extract the test and control lines of strips, the reflective integral optical density(IOD) is selected as the feature based on Lambert-beer law. The ratio (IODt/IODc) is directly proportional to the concentration of hCG in a sample by which the interference in the test and control lines can be cancelled out each other. We observe a good linearity(correlation of coefficient r = 0.98995) from the construction of standard curve throughout the entire measuring range 0-500mIU/ml, and the detection limit of the proposed method is enough sensitive to detect the hCG in the blood or urine of the pregnancy woman. The precision of the intra-assay expressed as coefficient of variation(CV) is below 12%. The system presented here takes less than 10min to perform from the sample treatment to the data analysis. Relative to scanning reflective optical system, our results suggest that a simple CCD-based imaging system can speed assay development, reduce errors, and improve accuracy. ©2010 IEEE. Source

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