MODELING AUTOMATED BLOOD COLLECTION SYSTEMS WITH BIOMETRIC IDENTIFICATION
DOI:
https://doi.org/10.30888/2663-5712.2020-06-01-039Keywords:
biometric identification, automatic system, dynamic methods, photoplethysmogram (PPG), blood sampling, perforation, classification of methods, structural-functional scheme, modeling.Abstract
This article substantiates the development of automated medical systems using biometric methods for identity identification. A structural and functional scheme was developed and 3D modeling of an automated biometric system of skin perforation with blood sMetrics
References
Seiden S.C., Barach P. Wrong-side/wrong-site, wrong-procedure, and wrong-patient adverse events: are they preventable? Arch. Surg. 2006; 14 (1): 931—9. DOI: 10.1001/archsurg.141.9.931
Henneman Ph.L., Fisher D.L. et al. Patient identifi cation errors are common in a simulated setting. Ann. Emerg. Med. 2010; 55 (6): 503-9. DOI: 10.1016/j.annemergmed.2009.11.017
I.Yakovenko, A. Rudoy and M.Turchyna, "IMPROVEMENT OF THE CREDIBILITY OF ANALYSIS OF ELECTROCARDIOGRAMS FOR BIOMETRIC PERSONAL IDENTIFICATION", Перспективні технології та прилади, no. 15, pp. 125-130, 2020. doi:10.36910/6775-2313-5352-2019-15-18.
I.Yakovenko, V.Martynenko and M.Turchyna,, "BIOMETRICAL IDENTIFICATION ON THE BASIS OF PHOTOPLETHYSMOGRAM FOR AUTOMATED MEDICAL SYSTEMS", Перспективні технології та прилади, no. 15, pp. 120-124, 2020. doi:10.36910/6775-2313-5352-2019-15-17.
І.О. Яковенко, К.П Вонсевич, І.Є. Гребень "Метод виділення ітерацій пульсових хвиль фотоплетизмограми для біометричної ідентифікації", Наукові вісті КПІ : міжнародний науковотехнічний журнал, № 3(2020), С. 73–78, 2020. DOI: 10.20535/kpi-sn.2020.3.209881
Y. Mamontov " Analysis and classification of photoplethysmograms using the Hopfield neural network ", Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriya: Informaczionny`e tekhnologii, vol. 12, no. 4, pp. 53-58, 2014.
K. Vonsevych, M. Bezuglyi and A. Haponiuk, "Evaluation of Electromyogram Time Characteristics of the Wrist Functional Movements for Intuitive Control of Bionic Prosthesis", Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute", vol. 0, no. 1, pp. 45-53, 2018. doi: 10.20535/1810-0546.2018.1.115941.
K. Vonsevych, M. Goethel, J. Mrozowski, J. Awrejcewicz and M. Bezuglyi, "Fingers Movements Control System Based on Artificial Neural Network Model", Radioelectronics and Communications Systems, vol. 62, no. 1, pp. 23-33, 2019. doi:10.3103/s0735272719010047.
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