Real Time Blood Type Determination by Gel Test Method on an Embedded System

Yıl 2016, Special Issue (2016), 412 - 415, 01.12.2016

Enes Ayan , Erdem Kamil Yıldırım

Öz

 This Determination
of a blood type has a crucial importance for blood transfusion. Therefore it is
mandatory doing tests to determine blood type before the transfusion. In order
to prevent the errors in determining blood type and to save time these tests
are carried out by the automatic devices. However these devices are very
expensive and it is necessary to develop cheaper alternative systems. In this
study, we designed a basic device which will be a first step for a cheap and
fast prototype. It utilizes the image processing techniques and gel test method
for real time blood type determination on embedded system. During the tests,
fifty gel test cards data were used and, it is found that the proposed system
can process each gel test card in 2 seconds with 99% accuracy on average.

Anahtar Kelimeler

Image Processing, Blood Types, Embedded Systems, OpenCv, Gel Test Method

Kaynakça

• [1] Lögdberg L, Reid ME, Zelinski T.,”Human blood group genes 2010: Chromosomal locations and cloning strategies” revisited. Transfus Med Rev, 25:36–46, 2011.
• [2] G. Daniels, Human Blood Groups, 2nd ed. Blackwell Science, 2002.
• [3] Malomgre W, and Neumeister B, “Recent and Future Trends in Blood Group Typing”, Anal Bioanal Chem, 393, 1443-1451, (2009)
• [4] Mujahid A, Dickert F.L, “Blood Group Typing: From Classical Strategies to the Application of Synthetic Antibodies Generated by Molecular Imprinting”, Sensors, 16-51, 2016
• [5] Zarifi T, Malek M.,”FPGA implementation of image processing technique for blood samples characterization”. Computers and Electrical Engineering (2013)
• [6] Ferraza, A., Carvalhoa, V., and Soaresa, F., (2010). “Development of a Human Blood Type Detection Automatic System”, Procedia Engineering, 5, 496–499.
• [7] Fathima, S. M. N., (2013). “Classification of Blood Types by Microscope Color Images”, International Journal of Machine Learning and Computing, 3, 376-379.
• [8] Dolmashkin, A., Dubrovskii, V. A., and Zabenkov, I. V., ”Blood Group Typing Based on Recording the Elastic Scattering of Laser Radiation Using the Method of Digital Imaging”, Quantum Electronics, 42, 409-416, (2012)..
• [9] Swarup, D., Dhot, P. S., Kotwal, J., and Verma A. K, (2008). “Comparative Study of Blood Cross Matching Using Conventional Tube and Gel Method”, Medical Journal Armed Forces India, 64, 129-130.
• [10] Toz G, Erdogmus P, Donmez K, “A Software Desıgn For Blood Groupıng By Usıng Gel Test Method”, Journal of Advanced Technology Sciences Vol 2, No 3, 100-109, 2013
• [11] Blood policy and technology, congress, office of technology assessment. Washington, DC, USA; FAS <http://www.fas.org/ota/reports/8505.pdf>;January 1985.
• [12] Sturgeon P.,” Automation: its introduction to the field of blood group serology”. Immunohematol J Blood Group Serol Educ 2001;17(4)
• [13] W. A. Coakly, Handbook of Automated Analysis, Mercel Dekker, 1981 pp. 6l.
• [14] Ewing GW, Analytical instrumentation handbook 2nd Ed. New York: Marcel Dekker; 1997. p. 152
• [15] Autoanalyzer,<http://www.sealanalytical.com/Products/AutoAnalyzerII/tabid/108/language/en-US/Default.aspx> ,(Accessed 2016)
• [16] Dia Pro Jel Kart, <http://www.diapro.com.tr/tr/urunlerimiz-across-gel.html>, (Accessed 2016).
• [17] <http://www.gokselmedical.com/WEB/DIAMED.doc>,