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Analysis of AVG signals
Mikauš, Jakub ; Čížek, Martin (referee) ; Rozman, Jiří (advisor)
MIKAUŠ, J. Analysis of AVG signals. Brno: Brno University of Technology,The Faculty of Electrical Engineering and Communication, 2008. 33 s., 1 příl. Supervisor of bachelors’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with AVG (arteriovelocitogram) signals analysis, that’s gained non-invasive measurment by the help ultrasound diagnostic equipments. The gained data of these signals are make use of specify diagnosis patients with ischemic disease. For this analysis is take advantage of algorithm using neural network of program enviroment MatLab. Variety topologies of multiply neural network were verified and results evaluated.
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Ultrasound blood flow detector
Šimák, Jakub ; Dlouhý, Jiří (referee) ; Rozman, Jiří (advisor)
Bachelor's thesis deals with design and electrical scheme of simple ultrasonic blood flow indicator, by which is possible get information of speed of blood without any invasion into patient's body. This device has been proposed for measure speed of blood in lower limbs, mainly patients with ischemic disease.
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Ultrasound blood flow detector
Šimák, Jakub ; Dlouhý, Jiří (referee) ; Rozman, Jiří (advisor)
Bachelor's thesis deals with design and electrical scheme of simple ultrasonic blood flow indicator, by which is possible get information of speed of blood without any invasion into patient's body. This device has been proposed for measure speed of blood in lower limbs, mainly patients with ischemic disease.
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Analysis of AVG signals
Mikauš, Jakub ; Čížek, Martin (referee) ; Rozman, Jiří (advisor)
MIKAUŠ, J. Analysis of AVG signals. Brno: Brno University of Technology,The Faculty of Electrical Engineering and Communication, 2008. 33 s., 1 příl. Supervisor of bachelors’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with AVG (arteriovelocitogram) signals analysis, that’s gained non-invasive measurment by the help ultrasound diagnostic equipments. The gained data of these signals are make use of specify diagnosis patients with ischemic disease. For this analysis is take advantage of algorithm using neural network of program enviroment MatLab. Variety topologies of multiply neural network were verified and results evaluated.
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