Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7590
Title: Teaching automated diagnostic systems for Doppler ultrasound blood flow signals to biomedical engineering students using MATLAB
Authors: Übeyli, Elif Derya
Güler, İnan
Keywords: [No Keywords]
Publisher: Tempus Publications
Abstract: This paper presents an initiative to teach the concept of automated diagnostic systems for Doppler ultrasound blood flow signals to biomedical engineering students. The approach was based on illustrative applications that highlight the performance of multilayer perceptron neural networks (MLPNN) and adaptive neuro-jazzy inference system (ANFIS). Following a brief description of the artificial neural networks (ANNs) and ANFIS, applications of the models to the Doppler signals ohtained from ophthalmic artery and internal carotid artery were done by means of a series of MATLAB functions. The functions involved in the neural network and fuzzy logic toolboxes of MATLAB can be used to develop automated diagnostic systems for the signal under study. The authors suggest that the use of MATLAB exercises will assist the students in gaining a better understanding of the various automated diagnostic systems in blood flow signals.
URI: https://hdl.handle.net/20.500.11851/7590
ISSN: 0949-149X
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

WEB OF SCIENCETM
Citations

6
checked on Mar 9, 2024

Page view(s)

46
checked on Mar 25, 2024

Google ScholarTM

Check





Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.