Degree Structure
College
Engineering
Department
Electrical Engineering
Level
Graduate Masters
Study System
Courses and Theses
Total Credit Hours
33 Cr. Hrs.
Duration
2-4 Years
Intake
Fall and Spring
Language
English
Study Mode
Full Time and Part Time
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Important Dates
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Degree Overview
The MSBME program accepts students from different undergraduate disciplines to be admitted to this program. As such, in order to provide the best learning experience to the graduate students regardless of their undergraduate background, the program is designed to help the student bridge the gap between their background and the MSBME program.
As a first step, the program provides 2 remedial courses based on the admitted student's bachelor's background. The remedial courses are chosen such that all students are prepared for the graduate core courses offered by the program. The graduate student is required to take the remedial courses in the first semester such that by the second semester all graduate students have the core-based information and background that qualifies them to continue towards the graduate core courses offered by the program. As an example: a student with B.Sc. in Medicine, Dentistry, or Health Sciences has enough biological background to continue forward with some MSBME courses; however, they fall short in the mathematical background from an engineering point of view. Therefore, they are required to successfully finish two remedial courses, "Differential Equations for Engineers" and "Mathematics for Engineers". The opposite goes for students with engineering background, where they fall short in biological background. Hence, they are required two remedial courses, "Human Anatomy and Physiology", and "Cell Biology". The same goes for students with science or pharmaceutical background, the MSBME program specifies to students their required remedial courses. Once the remedial courses are taken, all students are allowed to register for the graduate core courses.
It is advised that during the first year, students do not take any track electives till remedial and core courses are successfully passed.
Another issue that may raise a concern for graduate students from different bachelor's disciplines is the choice of elective courses from the 5 different tracks given in Fig. 5. The five tracks offered are:
1- Bioelectronics and Instrumentation, 2- Biomedical Systems and Feedback Control, 3- Applied Computational Bioengineering, 4- Biomedical Physics and Imaging, 5-Biomaterials, Cellular and Tissue Engineering.
Each track has a list of corresponding electives that are offered.
Students are advised to check the course description and if it has, any pre-requisite courses required.
If an elective course has pre-requisite courses listed before taking the graduate elective course, students wishing to take the course must prove they have the pre-requisite course taken during their bachelor's degree, or an equivalent course that qualifies them for the graduate elective course.
Before registering for an elective course, students are advised to talk to their supervisor, and the course instructor to check for any pre-requirement of the elective course.
For example, a student interested in taking "Biomedical Image Processing" needs to check the pre-requisites which are "Signals and Systems", and "Programming I". Students from electrical and computer engineering background have taken the pre-requisites during their bachelor's, so they can directly register for the course "Biomedical Image Processing".
However, students from science, medicine, or others, most likely did not take either course during undergraduate. Therefore, they are requested to check with course instructor to check if any equivalent courses were taken during undergraduate studies, or if they are required to take one or both courses before registering the elective.
For this, students are allowed to attend the undergraduate courses offered at the university with the recommendation of the course instructor, track co-coordinator and the program principle coordinator .
On this note, the completion of the program will take more than 2 years considering the need for any remedial courses for chosen track/elective courses.
The need for extra remedial courses will be faced by students desiring to divert from their bachelor's background. An engineer interested more in the biomaterial, cellular, and tissue engineering, or a pharmacist interested in the electronics behind biomedical research will require to build his knowledge in electronics and instrumentation before taking certain track electives.
Overall, the graduate students are strongly advised to refer to their academic advisor and track coordinators for guidance before taking decisions on registering for elective courses.
What You Will Learn
You will be able to solve medical challenges with engineered solutions in this MSc in Biomedical Engineering.
You'll study the way engineering can use and build on knowledge from medicine and life sciences, and master tissue engineering, biocompatibility, and health technology. You'll study with respected biomedical engineers, and have the opportunity to contribute to their active research projects in fields such as bio-inspired structures, healthcare monitoring, or prosthetic limb design.
When you graduate, you'll stand out in a growing and competitive field. You'll be able to identify and solve issues in health technology, demonstrate your practical abilities with biomedical hardware, and call on a network of experts, including your lecturers and fellow graduates.
University Requirements
College Requirements
Degree Requirements
Program Structure
| Requirement | Credit Hours |
| Compulsory (Core) Courses | 12 |
| Elective Courses | 12 |
| Thesis | 9 |
| Total Credit Hours | 33 |
Program Tracks
| Bioelectronics and Instrumentation |
| Biomedical Systems and Feedback Control |
| Applied Computational Bioengineering |
| Biomedical Physics and Imaging |
| Biomaterials, Cellular, and Tissue Engineering |
Study Plan: Course List
Compulsory (Core) Courses (12 credit hours)
| # | Course # | Course Name | Credit Hours | College/Dept. |
| 1. | 1440515 | Mathematical Methods for Bioengineering | 3 | Math |
| 2. | 0402580 | Introduction to Biomedical Engineering | 3 | All |
| 3. | 0402501 | Engineering Research Methodology | 3 | All |
| 4. | 0502500 | Hospital Labs Rotation | 2 | Medicine |
| 5. | 0402582 | Graduate Seminar | 1 | EE |
Elective Courses (12 credit hours)
Table 3 summarizes the list of elective courses offered under each track. With the guidance of their supervisor, students are free to choose the track most suitable to their interest.
"R = Recommended" and "O = Optional"
| Course Name | Credit Hours | Priority | College/Dept. |
| Bioelectronics and Instrumentation | |||
| Biomedical Sensors and Instrumentation | 3 | R | EE |
| Implantable Biomedical Microsystems | 3 | O | EE |
| Mixed Analog-Digital IC Design | 3 | R | EE |
| Advanced Signal Processing for Biomedical Engineering | 3 | O | EE |
| Biomedical Nanotechnology | 3 | O | EE/ Chem |
| Biomedical Systems and Feedback Control | |||
| Measurement and Instrumentation in Physiology and Medicine | 3 | R | MD/HS |
| Advanced Signal Processing for Biomedical Engineering | 3 | R | EE |
| Modelling in Physiology and Medicine | 3 | O | MD/CS |
| Linear and Non-Linear Multivariable Control System | 3 | O | EE/MD |
| Human-Machine Interaction | 3 | O | MD |
| Robotics and Dynamics control in Biomedicine | 3 | O | EE/MD |
| Neural Networks and Biomedical Applications | 3 | O | EE/MD |
| Robust Feedback Control | 3 | EE | - |
| Biomedical Image Processing | 3 | O | EE/MD/HS |
| Applied Computational Bioengineering | |||
| Statistics, Data Analysis and Algorithms in Genomic Biology | 3 | R | CS/MD |
| Applied Parallel Programming for Bioengineering | 3 | O | EE/CS/MD |
| Introduction to System Biology Modelling | 3 | O | CS/MD |
| Bioinformatics Networks | 3 | O | CS/MD |
| Machine Learning | 3 | O | CS/MD |
| Data Mining | 3 | O | CS/MD |
| Neural Networks and Biomedical Applications | 3 | O | EE/ MD |
| Biomedical Physics and Imaging | |||
| Medical Imaging and Instrumentation | 3 | R | HS/Phy |
| Biomedical Image Processing | 3 | R | EE/MD/HS |
| Molecular Imaging Application | 3 | O | MD/HS |
| Modelling in Physiology and Medicine | 3 | O | MD/CS/HS |
| Biomedical photonic | 3 | O | MD/Phy/Pharm |
| Radiation Measurements and Instrumentation | 3 | O | NE/HS/Phy |
| Advanced Radiobiology and Radiation Protection | 3 (2+1) | O | HS/Phy/NE |
| Biophysics | 3 | O | HS/MD |
| Principles of Tissue Engineering and Gene Therapy | 3 | O | MD/Biotech |
| Biomaterials, Cellular, and Tissue Engineering | |||
| Principles of Tissue Engineering and Gene Therapy | 3 | R | MD/Biotech |
| Advanced Cell Biology | 3 | R | Biotech |
| Bioinformatics Networks | 3 | O | CS/MD/Biotech |
| Biomaterials for Medical Applications | 3 | O | CH/ ME |
| Cellular and Molecular Neuroscience | 3 | O | MD |
| Novel Drug Delivery Systems | 3 | O | Pharm |
| Stem Cell Biology and Engineering | 3 | O | Biotech |
| General Electives | |||
| Independent Studies in Biomedical Engineering | 3 | O | ALL |
| Selected Topics in Biomedical Engineering | 3 | O | ALL |
| Commercialization of Biomedical Innovation | 3 | O | ALL |
| Healthcare Operation, Planning, and Risk Management | 3 | O | ALL |
Thesis (9 credit hours)
Students to enroll in the proposed program will have to prepare an extensive graduation report based on actual research work conducted at the research labs of faculty supervising the student or fieldwork under the supervision of a faculty members involved with the program. The report will account for (be equivalent to) nine credit hours of the program and will have to be enrolled in during the fourth semester of the study program.
Remedial Courses
As a first step, the program provides two remedial courses based on the admitted student's bachelor's background as shown in Table 6. The remedial courses are chosen such that all students are prepared for the graduate core courses offered by the program. It is advised that during the first year, students do not take any track electives till remedial and core courses are successfully passed.
Table 6: Remedial courses list for different undergraduate disciplines joining the M.Sc. in Biomedical Engineering program
| Course No. | Course Name | Credit Hours (CH) | College/Dept. |
| Bachelor's Degree in Engineering or Science (except Biotechnology) | |||
| 0901720 | Human Anatomy and Physiology | 2+1 | Medicine |
| 1450251 | Cell Biology | 3 | Biotechnology |
| Bachelor's Degree in biotechnology | |||
| 0901720 | Human Anatomy and Physiology | 2+1 | Medicine |
| 1440262 | Mathematics for Engineers | 3 | Math |
| Bachelor's Degree in medicine, Dental Medicine, or Health Science | |||
| 1440261 | Differential Equations for Engineers | 3 | Math |
| 1440262 | Mathematics for Engineers | 3 | Math |
| Bachelor's Degree in pharmacy | |||
| 1440262 | Mathematics for Engineers | 3 | Math |
| 1450251 | Cell Biology | 3 | Biotechnology |
Course Description
| 0402580 | Introduction to Biomedical Engineering | 3 Credit Hours |
| This course serves as an introduction to and overview of the field and areas of biomedical engineering. The biomedical engineering areas such as bioelectric phenomena, bioinformatics, biomaterials, biomechanics, bioinstrumentation, biosensors, biosignal processing, biotechnology, computational biology and complexity, genomics, medical imaging, optics and lasers, radiation imaging, tissue engineering, and moral and ethical issues will be covered in this course. | ||
| Historical perspective of the major developments in a specific biomedical engineering domain as well as the fundamental principles that underlie biomedical engineering design, analysis, and modeling procedures in that domain are also included. In addition, examples of some of the problems encountered, as well as the techniques used to solve them, are provided. | ||
| 1440515 | Mathematical Methods for Bioengineering | 3 Credit Hours |
| The course offers mathematical methods for solving application problems in biomedical engineering, including computational techniques centered at many aspects of systems biology and bioengineering research. | ||
| Mathematical concepts related to modelling of physiological bio-molecular processes are considered. It will cover the fundamental technique to Ordinary Differential Equations (ODE) using Laplace transformation, Fourier series, integrals, and solve Partial Differential Equations (PDE) including Bessel function, Legendre polynomials, and introduce complex analysis. | ||
| Theory of supervised and unsupervised learning, Monte Carlo computation, analysis of gene expression data and genome sequence data. The course will also cover classical equations for mathematical physics: heat equations, wave equations, and potential equations. Representation and analysis of bio-signals, biological fluid mechanics, pharmacokinetics and mathematical diffusion will be covered as well. Numerical solving will be based on the use of MATLAB. | ||
| 0402501 | Engineering Research Methodology | 3 Credit Hours |
| Students learn how to apply the engineering research process and methods of inquiry to solve engineering problems. Literature survey for research work, building expertise in the areas of interest, this involves critiquing current research work. Basic principles of experimental designs; analyze and evaluate the results. Evaluate the quality of the results and limitations. | ||
| They will also learn how to communicate findings in specific engineering formats to specialist audiences. Students will learn basic project management and teamwork skills in addition to research ethics. Course project will allow the students to apply research methodology components on research problems of their choice. Students, possibly in small teams, are expected to present and defend their research proposals. | ||
| 0502500 | Hospital Lab Rotation | 2 Credit Hours |
| Masters students in Biomedical Engineering are required to take lab rotations at the University Hospital Sharjah (UHS). This non-credit course will introduce the students to biomedical equipment and tools used in various clinical departments. For example, the students will rotate in the anesthesia and surgical department, interventional and stress-test cardiovascular procedures labs, orthopedic and physical rehabilitation facilities, radiology department, medical diagnostic labs, and central hospital laboratory. | ||
| 0402582 | Graduate Seminar | 1 Credit Hours |
| Students are required to attend seminars given by faculty members, visitors, and fellow graduate students. Each student is also required to present a seminar outlining the research topic of the master thesis. | ||
| 0402600 | Master Thesis | 9 Credit Hours |
| The student has to undertake and complete research topic under the supervision of a faculty member. The thesis work should provide the student with an in-depth understanding of a research problem in Biomedical Engineering. It is expected that the student, under the guidance of the supervisor, will be able to conduct research somewhat independently, and may also be able to provide solution to that problem. | ||
| 0402583 | Biomedical Sensors and Instrumentation | 3 Credit Hours |
| This course will identify basic principles involved in biomedical sensors instrumentation, mechanisms of different sensors, their classification, regulation and ethical use. Biosensors principles, types and properties, performance factors in biosensors, enzymatic biosensors etc. Development of an understanding of the measurement principles of medical instrumentation, including noise-filtering instrumentation amplifier, computer control, sampling, data collection of bioelectrical signals (ECG, EEG, EMG), measurement of respiratory function, cardiac variables, blood pressure, and blood flow. | ||
| This knowledge will be applied to solve real world problems of medical device development, troubleshooting, and the identification of ethical principles in the use of medical sensors in patient care. | ||
| 0402584 | Implantable Biomedical Microsystems | 3 Credit Hours |
| A general overview on the multi-disciplinary field of implantable biomedical microsystems is introduced in the course. The material to be covered comprises extensive contents and in-depth discussions on both system- and circuit-level aspects of the design of implantable microsystems. This includes wireless interfacing, microelectrode array fabrication, and circuit design for implantable neural recording microsystems. | ||
| Different design aspects of neural stimulation microsystems, cochlear implants, and visual prostheses are also reviewed briefly. Key issues of biomaterial/tissue interactions such as foreign body response and biocompatibility and biocompatibility assessment are covered. Issues concerned with design for implantability and envisions for testability are also dealt with. | ||
| 0402585 | Mixed Analog-Digital IC Design | 3 Credit Hours |
| This course will provides a solid understanding and an overview of analog and mixed-signal integrated circuit analysis, design, simulation, and layout consideration for Low frequency applications. Examination of Gilbert multipliers; operational amplifiers; frequency compensation techniques; advanced biasing techniques; voltage references; and mixed-signal systems such as compactors and data converters including analog-to-digital converters (ADC) and digital-to-analog converters (DAC). | ||
| Students will learn transistor-level design of analog and digital circuits, layout techniques for analog and digital circuit modules, and special physical considerations that arise in a mixed-signal integrated circuit. Students will design a custom mixed-signal integrated circuit over the semester in the course project that will be submitted at the end of the semester. | ||
| 0402586 | Advanced Signal Processing for Biomedical Engineering | 3 Credit Hours |
|
Introduction to advanced concepts in biomedical signal processing that go beyond the conventional analysis of linear, stationary, normal signals. Allow students to develop computational algorithms for analysis of clinically relevant physiological signals. Identifying modern signal processing tools used to analyze major physiological signals in order to investigate the generation, the form, the dynamics and the information content of the signals; and draw diagnostics/prognostic conclusions, based on quality signal processing, about the normality and abnormality of the organ systems. |
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| 0402593 | Applied Parallel Programming for Bioengineering | 3 Credit Hours |
|
Introducing fundamental issues in design and development of parallel programs for various types of parallel computers. The course will cover various programming models including linear programming based on SSR (Sequence Selection and Repetition) according to both machine type and application area. Cost models, debugging, and performance evaluation of parallel programs with actual application examples. Parallel programming with emphasis on developing applications for processors with many computation cores. Computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies from the bioengineering High-Performance Application field. |
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| 0900720 | Introduction to System Biology Modelling | 3 Credit Hours |
| The goal of this course is to highlight elementary design principles inherent in biology. Many of the underlying principles governing biochemical reactions in a living cell can be related to network circuit motifs with multiple inputs/outputs, feedback and feedforward. This course introduces the student to methods that can be used to tackle complex systems head-on using case studies that comprise the foundation of systems biology. The initial lectures of the course focus on bringing students quickly up to speed with a variety of modeling methods in the context of a synthetic biological circuit. This is later applied on much more complicated network models are addressed—including transcriptional, signaling, metabolic, and even integrated multi-network models. In order to achieve those objectives the course introduces the student to mathematical techniques for quantitative analysis and simulations of basic circuits in genetic regulation, signal transduction, and metabolism. Several continuous and discrete mathematical models such as ordinary, partial differential equations, dynamical systems and stochastic processes are used to formulate evolutionary biological models. Numerical methods are used in explaining the self-organization of biological networks; and biochemical simulations are discussed using recent and suitable software. The course will use case studies on topics that include end-product inhibition in biosynthesis, optimality and robustness of the signaling networks and kinetic proofreading. | ||
| 0900707 | Bioinformatics Networks | 3 Credit Hours |
| This course will introduce students to Biological databases especially GenBank at the NCBI in addition to some of the most commonly used software and tools for genetic analysis of nucleic acid, protein sequences and designing primers and probes for PCR. In addition, the course explores and explains some of the computational biology tools found on the Internet and how they can be applied to problems in genomics and molecular biology to extract genomic signature that can shed light on the molecular mechanism of disease. | ||
| 1411531 | Machine Learning | 3 Credit Hours |
| This course provides a broad introduction to machine learning. Topics include Regression: Simple and Multiple, Ridge, Kernel Feature, Feature Selection Lasso; Classification: supervised learning such as Linear Classifiers Logistic Regression; Decision Trees, support vector machines, and neural networks; unsupervised learning (such as clustering, recommender systems, deep learning); and best practices in machine learning such as Overfitting/Regularization and bias/variance theory. | ||
| 1411565 | Data Mining | 3 Credit Hours |
| Data mining has become one of the most interesting and rapidly growing fields. Data mining techniques are used to uncover hidden information, such as patterns, in databases and perform predictions. The data to be mined may be complex data including multimedia, spatial, and temporal. Topic include data processing, association rules, clustering, and classification. This course is designed to provide graduate students with a solid understanding of data mining concepts and tools. | ||
| 0502502 | Medical Imaging and Instrumentation | 3 Credit Hours |
| This course covers the physics, equipment and technical principles underlying the following medical instrumentation methods: tissue culture and in vitro imaging, X-ray radiography, computed tomography (CT), single photon and positron emission tomography (SPECT), positron emission tomography (PET) including SPECT/CT and PET/CT, magnetic resonance imaging (MRI), ultrasound (US) and doppler imaging techniques. It will also address the mathematical framework describing image encoding/decoding, point-spread function/modular transfer function, signal-to-noise ratio, contrast behavior for each of the medical imaging modalities. The use of commercial software is advised for the implementation and study of basic concepts. | ||
| 0502503 | Molecular Imaging Application | 3 Credit Hours |
| This course introduces a new discipline that combines cell biology, molecular biology, and diagnostic imaging. Two basic applications of molecular imaging are diagnostic imaging and therapeutic. This course will focus on the role of diagnostic imaging in detecting molecules, genes, and cells in vivo that are specific to a disease; mainly by the ability to identify receptor sites related to target molecules characterizing the disease studied. Emphasis will be on how these molecular imaging techniques can help study molecular mechanisms of disease in vivo. Topics include DNA/protein synthesis, transgenic mice, novel contrast agents and small animal imaging. | ||
| 1430501 | Biomedical Photonics | 3 Credit Hours |
| This course studies interaction between light and biological materials; it then uses the information gathered to search and study for non-invasive diagnostic methods. The course should provide knowledge about light sources and light delivery systems, optical biomedical imaging techniques, optical measurement technologies and their specific applications in medicine. Fundamental principles will be accompanied by practical and contemporary examples. Different selected optical systems used in diagnostics and therapy will be discussed, new techniques for live cell imaging used in early diagnosis for cancer, diabetes, or other diseases will be also reviewed. Fluorescent probes and some nanotechnology applications like quantum dots will be included. | ||
| 0407550 | Radiation Measurements and Instrumentation | 3 Credit Hours |
| This course covers a background in therapeutic radiotherapy instrumentation, dosimetry and treatment planning. Clinical radiation generators considered include kilovoltage units, Van de Graafs, Linacs, beatatron, microtron, cyclotron and radionuclide based units. Means for dose measurement using ionization chambers, solid state detectors (TLD), calorimetry, film and chemical dosimetry as well as dosimetric calculation methods employing depth doses, tissue air ratios, tissue maximum ratios, irregular field techniques and methods for inhomogeneity corrections. The concept of Monte Carlo will be introduced through simulation lab to help students understand the characteristics of ionizing radiation in simple and complex situations. | ||
| 0502501 | Advanced Radiobiology and Radiation Protection | 3 Credit Hours |
| The course covers the basic principles of ionizing radiation and its physical and biological effects. The physical interactions of photons as well as of charged particles; the factors which underpin the differing radio-sensitivities of different tumors and normal tissue versus tumor tissue; fundamentals in dosimetry; deterministic as well as stochastic effects; and fundamental knowledge about radiation protection. Generation of ionizing radiation including the x-ray tube, the clinical linear accelerator, and different radioactive sources in radiology, and radiotherapy are addressed. Applications in radiology, clinical radiotherapy, and radiation protection are studied through practical scenarios. | ||
| 1401020 | Computational Data Analysis for Bioengineering | 3 Credit Hours |
| Fundamentals of data analysis in bioengineering, including statistical methods, hypothesis testing, and model fitting. Methods include regression analysis, ANOVA, Bayesian statistics, and machine learning approaches for high-dimensional data. Applications of these methods to bioengineering problems, such as genomics, proteomics, and imaging data analysis, will be emphasized. The course will include hands-on experience with software tools for data analysis. | ||
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