Biomedical Engineering and Medical Devices Research Group - International Burch University
 

Biomedical Engineering and Medical Devices Research Group

About

The main research focus is the development and application of modern signal, imaging, computing, electronics and other technologies in biomedicine, especially in three areas: biomedical imaging, biosignal processing, and therapeutic technologies. Examples include but are not limited to magnetic resonance imaging (MRI) and molecular imaging, ultra-high speed biophotonic imaging, ultrasound strain and shear wave imaging, therapeutic ultrasound, bioinformatics, neural engineering, computational neuroscience, extraction and detection of weak evoked potential signals, artificial neural network filters and wavelet methods, and blind signal method for biosignal estimation.

Background and Motivation

The Group originated in 2009. with the aim of promoting research in the emerging field of Biomedical Engineering, a profession that applies the principles of the science of physics/engineering directly to the design and operation of the complex medical devices used in the diagnosis and treatment of the sick and injured. The group has close collaborations with scientists and clinicians with world-renowned academic and clinical institutions.

Research

The main research activities of the Biomedical Research Group are primarily focused on the understanding, development, and applications of instrumentation, sensors and physiological measurements to facilitate the prognosis, diagnosis, and treatment of a disease or the rehabilitation of patients. The research pushes the frontiers of current optical and electronic technologies and demonstrates how such technologies can be used as medical "tools". Challenges from various clinical specialties are being addressed, leading to interdisciplinary applications of advanced and novel technologies. Moreover, the aim of this research group is to propose and develop a strategic framework for the development of biomedical engineering area in Bosnia and Herzegovina. That will be achieved through implementation of projects in cooperation with non-governmental and governmental bodies in our countries and international conferences.

Vision

The vision of the group is twofold. Firstly, in a more fundamental way, is to provide further basic knowledge in the interaction of light with biological tissue which will have a direct impact on the understanding of so far unexplained pathophysiological phenomena and processes. Secondly, in a more applied way, to create a center of excellence in the area of design, development and evaluation of novel medical instrumentation. The output of such developments will lead in the commercialisation of novel technologies that will be used in the hospital or homecare setting.

People
Assis. Prof. Dr. Jasmin Kevrić
Assis. Prof. Dr. Almir Badnjević
Dino Kečo, PhD candidate
Zerina Mašetić, PhD candidate
Samed Jukić, PhD candidate
Adnan Hodžić, PhD candidate
Lejla Gurbeta, PhD candidate
Lejla Bandić
Damir Bilić
Aiša Ramović
Mehmed Đug
Fatima Mašić
Ahmed Osmanović
Layla Abedel-Ilah
Berina Alić
Dijana Sejdinović
Zerina Đozić
Dalibor Đumić
Ermin Podrug
Faruk Ćidić
Sead Banda
Hadi Nourallah
Publications

JOURNALS

Accepted/Published Articles in SCI indexed Journals (Peer-review)

Jasmin Kevric, Abdulhamit Subasi; Comparison of Signal Decomposition Methods in Classification of EEG Signals for Motor-imagery BCI System, Biomedical Signal Processing and Control, Vol. 31, Sep. 2016
Z. Masetic, A. Subasi; Congestive heart failure detection using random forest classifier, Computer Methods and Programs in Biomedicine, Vol. 130, Jul. 2016
M. R. Bozkurt, A. Subasi, E. Koklukaya, M. Yilmaz, “Comparison of AR parametric methods with subspace-based methods for EMG signal classification using stand-alone and merged neural network models”, (Accepted Turkish Journal of Electrical Engineering & Computer Sciences)
E. Alickovic, A. Subasi, “Effect of Multiscale PCA de-noising in ECG beat classification for diagnosis of cardiovascular diseases”, Circuits Systems and Signal Processing, Feb. 2015, Vol. 34, Issue 2, 513-533.
E. Gokgoz, A. Subasi, Comparison of decision tree algorithms for EMG signal classification Biomedical Signal Processing and Control, 18 (2015), 138–144.
A. Subasi, A decision support system for Diagnosis of Neuromuscular Disorders using Evolutionary Support Vector Machines, Signal, Image and Video Processing, Vol. 9, Issue 2 (2015), Page 399-408.
J. Kevric, A. Subasi, “The Effect of Multiscale PCA De-noising in Epileptic Seizure Detection”, Journal of Medical Systems, 38(10):131, 1-13, 2014.
E. Gokgoz, A. Subasi, “Effect of Multiscale PCA de-noising on EMG signal classification for Diagnosis of Neuromuscular Disorders ”, Journal of Medical Systems, 38(4):31,1-10, April 2014.
A. Subasi, Classification of EMG Signals Using PSO optimized SVM for Diagnosis of Neuromuscular Disorders, Computers in Biology and Medicine 43 (2013) 576–586. (Times Cited in Web of Science: 12)
A. Subasi, Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines, Computers in Biology and Medicine 42, 806–815, 2012. (Times Cited in Web of Science: 8)
A. Subasi, “Classification of EMG Signals Using Combined Features and Soft Computing Techniques”, Applied Soft Computing, 12, 2188–2198, 2012. (Times Cited in Web of Science: 10)
S. B. Akben, A. Subasi, D. Tuncel, “Analysis of repetitive flash stimulation frequencies and record periods to detect migraine using artificial neural network”, Journal of Medical Systems, 36(2), 925-931, 2012. (Times Cited in Web of Science: 1)
S. B. Akben, A. Subasi, D. Tuncel, “Analysis of EEG Signals under Flash Stimulation for Migraine and Epileptic Patients”, Journal of Medical Systems, 35(3), 437-443, 2011. (Times Cited in Web of Science: 6)
A. Subasi, M. I. Gürsoy, “Comparison of PCA, ICA and LDA in EEG signal classification using DWT and SVM”, Expert Systems with Applications, 37, 8659–8666, 2010. (Times Cited in Web of Science: 50)
A. Subasi, M. K. Kiymik, “Muscle Fatigue Detection in EMG Using Time–Frequency Methods, ICA and Neural Networks”, Journal of Medical Systems, Volume 34, Number 4, 777-785, 2010. (Times Cited in Web of Science: 10)

Accepted/Published Articles in non-SCI Journals (Peer-review)

Inspection Process of Medical devices in Healthcare institutions: Software Solution, L. Gurbeta, A. Badnjevic, Health and Technology Journal – in press
Testing of mechanical ventilators and infant incubators in healthcare institutions, Almir Badnjevic, Lejla Gurbeta, Elvira Ruiz Jimenez, Ernesto Iadanza, Journal: Transaction on Biomedical Engineering – in press
Jasmin Kevric, Abdulhamit Subasi; The Impact of MSPCA Signal De-noising In Real-Time Wireless Brain Computer Interface System,
Southeast Europe Journal of Soft Computing, Vol. 4, No. 1, Mar. 2015 Z. Masetic, A. Subasi, Detection of congestive heart failures using C4.5 Decision Tree, Southeast Europe Journal of Soft Computing, 2(2), 74-77, 2013.
S. Jukic, A. Subasi, Localization of the epileptogenic foci using Support Vector Machine, Southeast Europe Journal of Soft Computing, 2(2), 26-30, 2013.

CONFERENCES

International conferences:
Badnjević A, Gurbeta L; Development and Perspectives of Biomedical Engineering in South East European Countries, 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (IEEE MIPRO), At Opatija, Croatia, 2016
Testing of therapeutic ultrasound in healthcare institutions in Bosnia and Herzegovina, Lejla Gurbeta, Almir Badnjevic, Zijad Dzemic, Elvira Ruiz Jimenez, Alma Jakupovic, EAI Conference – Fabulous 2016 Belgrade
Software Solution for Tracking Inspection Processes of Medical Devices from Legal Metrology System, Gurbeta L, Sejdinović D, Alić B, Abd El Ilah L, Badnjević A, Žunić E, Meditereninan Conference on Medical and Biological Engineering and Computing, MEDICON, Cyprus 2016
Mustoo S., Gurbeta L.; Turning the Challenge into Opportunity – A Strategic Framework for the Biomedical Engineering Development in Bosnia and Herzegovina, Folia Med. Fac. Med. Univ. Saraeviensis 2015; 50(1): 18-22
Boskovic D, Badnjevic A. „Opportunities and Challenges in Biomedical Engineering Education for Growing Economies“, IEEE 4th Mediterranean Conference on Embedded Computing (MECO), pp: 407-410, 14 – 18 June 2015, Budva, Montenegro
Software Package for Tracking Status of Inspection Dates and Reports of Medical Devices in Healthcare Institutions of Bosnia and Herzegovina, Gurbeta L., Badnjević A., Žunić E., Pinjo N., Ljumić F., Information, Communication and Automation Technologies (ICAT), 2015 XXV International Conference, vol., no., pp.1-5, 29-31 Oct. 2015, doi: 10.1109/ICAT.2015.7340532
Medical devices in legal metrology, Badnjevic A., Gurbeta L., Boskovic D. and Dzemic Z., 4th Mediterranean Conference on Embedded Computing MECO 2015, At Budva, Montenegro, Volume: ISBN 978-1-4799-8999-7, 365 – 367, DOI: 10.13140/RG.2.1.4741.2324
Measurement in medicine – Past, present, future, Badnjevic A., Gurbeta L., Boskovic D. and Dzemic Z., Folia Med. Fac. Med. Univ. Saraeviensis 2015; 50(1): 43-46
N. Arnaut, A. Subasi, Sleep stage classification using AR Burg and C4.5 classifier, The 1st Conference of Medical and Biological Engineering in Bosnia and Herzegovina (CMBEBIH 2015), 13-15 March 2015, Sarajevo, Bosnia and Herzegovina.
E. Podrug, A. Subasi, Surface EMG pattern recognition by using DWT feature extraction and SVM classifier, The 1st Conference of Medical and Biological Engineering in Bosnia and Herzegovina (CMBEBIH 2015), 13-15 March 2015, Sarajevo, Bosnia and Herzegovina.
Z. Masetic, A. Subasi; Detection of congestive heart failures using C4.5 Decision Tree, Southeast Europe Journal of Soft Computing, Vol. 2, No. 2, Sep. 2013
E. Alickovic, A. Subasi, Comparison of decision tree methods for breast cancer diagnosis, The 6th International Conference on Information Technology (ICIT 2013), Amman, Jordan, May. 2013
J. Kevric, A. Subasi, Classification of EEG signals for epileptic seizure prediction using ANN, ISSD’12, Third International Symposium on Sustainable Development, Sarajevo, Bosnia and Herzegovina, 2012.
H. Sahin, A. Subasi,Classification of fetal state from the cardiotocogram recordings using ANN and simple logistic, ISSD’12, Third International Symposium on Sustainable Development, Sarajevo, Bosnia and Herzegovina, 2012.
E. Alickovic, A Subasi, Medical decision support system for diagnosis of cardiovascular diseases using DWT and k-NN, ISSD’12, Third International Symposium on Sustainable Development, Sarajevo, Bosnia and Herzegovina, 2012.
S. Keleş, A. Subasi, Classification of EMG signals using decision tree methods, ISSD’12, Third International Symposium on Sustainable Development, Sarajevo, Bosnia and Herzegovina, 2012.
E. Aličković, A. Subasi, “Data Mining Techniques for Medical Data Classification”, The International Arab Conference on Information Technology (ACIT) 2011.
Projects

1. Project

Project Name:
International Conference on Medical and Biological Engineering, CMBEBIH 2017


2. Project

Project Name:
EMG based man–machine interaction-A Platform for Classification of Myoelectric Signals for Prosthesis Control

Supported by: International Burch University

3. Project

Project Name:
Comparison of Different Feature Extraction and Machine Learning Techniques in EEG-Based Wireless BCI System

Supported by: International Burch University,

4. Project

Project Name:
New Approaches for Diagnosis of Brain Diseases Using Different Image Processing and Data Mining Techniques

Supported by: International Burch University,

5. Project

Project Name:
Comparison of Machine Learning Methods for Biomedical Signal Analysis

Supported by: International Burch University,