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Sensors 2016, 16(7), 1007;

Development of a Calibration Strip for Immunochromatographic Assay Detection Systems

1,2,†,* , 1,2,3,†
College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China
Key Lab of Medical Instrumentation & Pharmaceutical Technology of Fujian Province, Fuzhou 350116, China
State Key Laboratory of Analog and Mixed Signal VLSI, University of Macau, Macau 999078, China
Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Mun’delanji Vestergaard
Received: 16 May 2016 / Revised: 14 June 2016 / Accepted: 21 June 2016 / Published: 29 June 2016
(This article belongs to the Special Issue Point-of-Care Biosensors)
Full-Text   |   PDF [2785 KB, uploaded 29 June 2016]   |  


With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R2 = 98.78%). View Full-Text
Keywords: calibration strip; immunochromatographic (ICG) assay; fuzzy c-means (FCM) algorithm; maximin-distance algorithm calibration strip; immunochromatographic (ICG) assay; fuzzy c-means (FCM) algorithm; maximin-distance algorithm

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Gao, Y.-M.; Wei, J.-C.; Mak, P.-U.; Vai, M.-I.; Du, M.; Pun, S.-H. Development of a Calibration Strip for Immunochromatographic Assay Detection Systems. Sensors 2016, 16, 1007.

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