As a Biomedical Engineering (BME) major at Duquesne, you'll be challenged in the classroom
and the lab, preparing to make an impact in the field after graduation. Our students
receive a Bachelor of Science Degree, majoring in Biomedical Engineering and a minor
in Mathematics while:
Gaining broad-based engineering fundamentals combined with hands-on research on biomedical
optics and sensors, with applications in oncology, orthopedics, ophthalmology, dermatology
and other areas of medicine
Mastering mathematical methods, programming and fabrication of protytpe medical devices
Honing your skills in critical thinking, problem-solving, communication and management
Understanding the increasing importance of leadership and ethics in the engineering
You want to change the world—we'll help you do it. Biomedical engineering, like any
branch of engineering, uses scientific and mathematical principles to solve problems
facing the world. BME focuses on improving human health across distinct areas, like
biomedical optics, biomaterials, orthopedic biomechanics, biophysical interactions,
drug delivery and biosensor development.
As a graduate of our biomedical engineering program, you will:
Achieve productive and satisfying employment in a biomedical engineering-related field
Obtain entry into a graduate or professional-degree granting program
Maintain professional competence within their industry
Be well-versed in a professional and ethical manner with an attentiveness to service
On a national level, the Occupational Outlook Handbook 2014 - 2024 (US Bureau of Labor
Statistics) indicates the field is growing much faster than average. Biomedical engineers
are also among the Fastest Growing Occupations in Pennsylvania 2008-2018.
Upon graduation, you'll have acquired the ability to:
Identify, formulate, and solve complex engineering problems by applying principles
of engineering, science, and mathematics
Apply engineering design to produce solutions that meet specified needs with consideration
of public health, safety, and welfare, as well as global, cultural, social, environmental,
and economic factors
Communicate effectively with a range of audiences
Recognize ethical and professional responsibilities in engineering situations and
make informed judgments, which must consider the impact of engineering solutions in
global, economic, environmental, and societal contexts
Function effectively on a team whose members together provide leadership, create a
collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
To develop and conduct appropriate experimentation, analyze and interpret data, and
use engineering judgment to draw conclusions
Course Descriptions & Curriculum
The curriculum includes 133 Credit Hours, including 52 credit hours of engineering
content. In addition to math, science courses and labs and the Bridges Common Learning
Experience, students will take the following engineering courses (courses subject
This course introduces the academic discipline of biomedical engineering using software
tools that emphasize design, measurment, and analysis. Various software tools and
hardware will be used to explore aspects of science and engineering that will be used
and developed later in the undergraduate curriculum. Students will gain experience
with PIC microprocessors and hardware interfacing, instrumentation control, and solid
modeling with Fusion 360. This course is project oriented with application for measurement
and testing biological media.
This course introduces software tools and scientific programming techniques so that
the student may make use of the powerful computing environments now commonly available.
The course uses Matlab for study of scientific computation. Matlab is used to show
programming methods, as well as to introduce numerical techniques. The objective is
directed towards scientific programs for solutions of engineering equations, analysis
of data, and simulation of physical phenomena. Software design includes mastering
flow control, conditional statements, input and output, two and three dimensional
graphics, and data structures. Additionally, the student will apply these software
constructs to solve problems in statistics, imaging, and problems in biomedical engineering.
This course covers basic analog and digital electronics and laboratory instrumentation
with medical device design in mind. This course will include the theory and applications
of passive and active analog and digital circuits with devices, such as; Basic RLCs,
BJTs, MOSFETs, Diodes, the Zener Diode, Operational Amplifiers, Voltage Comparators,
Logic ICs, LEDs, the Piezo Element Speaker, Potentiometers, Switches, the Temperature
Sensor, the Relay, the Photo-Resistor, the DC Motor and the DC Servo Motor, along
with basic Electronic Instrumentation. Also included in this course are DC, Transient
and AC Sinusoidal circuit analysis, using Thevenin and Norton equivalency, the Final
Value Theorem and Complex Variables. Additionally, this course will examine various
Signal Conditioning Interface circuits, which are commonly used in microcontroller
applications. This course will also include experiments with the Arduino/Atmel Microcontroller,
using the above-mentioned devices and C-Code programming, using the Arduino C-Code
Using BMED-201 as a foundation, this course will focus on a larger scale integration
of electronics and electronic laboratory instrumentation, using the PIC Microcontroller.
The student will learn the basics of the PIC Microcontroller by programming it with
Assembly Code, C-Code and PIC-Basic Pro Code. The student will gain a larger understanding
of various Analog and Digital Interface circuits, Signal Conditioning Circuits and
General Data Acquisition Circuits, using Basic RLCs, BJTs, MOSFETs, Diodes, Zener
Diodes, Operational Amplifiers, Voltage Comparators, Logic ICs, LEDs, the Crystal,
the Text Liquid Crystal Display (TLCD), the IR-LED, the IR-Photo-Transistor, a Speaker,
a Voltage Regulator, a 4-Phase Stepper-Motor, a Brushless DC-Fan Motor and a Relay,
along with the PIC Microcontroller. All of the above will be presented with medical
device design in mind.
Application of principles drawn from thermodynamics are critical in the design of
biomedically-relevant devices. This course covers the laws of Thermodynamics and provides
tools for working relevant engineering problems in energy and material conservation.
This course makes use of Matlab software.
Biomaterials are increasingly found in medical applications. This course covers basic
concepts of biomaterials by studying mechanical and biological properties of soft
and hard materials used in medical science and medicine. The surface chemistry approach
will be taken in this course with regard to understanding, analyzing, and using biomaterials.
This course provides a rigorous coverage of signal and systems with applications in
biomedical engineering. Basic concepts, such as continuous and discrete time systems,
Fourier and Laplace transforms and their discrete counterparts, are explored. Problems
are motivated by biomedical signal and image processing, as well as in other linear
systems encountered in biomedical engineering. Students will use Matlab and Simulink.
This course covers fluid statics and dynamics, with particular emphasis on systems
encountered in biomedical engineering. Not only are fluid systems found in the human
body covered, such as blood flow, but engineering systems, such as microfluidic devices,
are explored too.
This course introduces mathematical and computational techniques that are relevant
for describing and modeling physical processes encountered in biomedical engineering.
Topics will include ordinary and partial differential equations, matrix methods including
the singular value decomposition, and integral transforms, such as Fourier and Wavelet.
Mathematical methods will be introduced within the context of current problems in
biomedical engineering. For instance, numerical solutions to the diffusion equation
will be developed during study of heat conduction in tissue. Similarly, edge enhancement
techniques using the wavelet transform will be shown in medical images. This course
makes extensive use of Matlab.
This course focuses on utilizing computational methods to solve engineering problems,
which often can't be solved analytically. The goal of this course is to provide students
a comprehensive understanding of a variety of computational methods and algorithms.
Those methods will be introduced in the context of engineering examples, and implemented
in MATLAB. Advanced MATLAB programming techniques will be introduced to solve complex
engineering problems. Topics of this course includes: errors, roots and optimization,
curve fitting, integration, and differentiation. Advanced topics may also be introduced.
The capstone is the culmination of the educational process in biomedical engineering.
In this phase, a problem in biomedical engineering is studied by a student team, and
the team provides an engineering solution. This solution will often be a medical device.
Students perform deterministic and statistical studies of the problem and design the
solution. Prototype construction will begin during this phase of the project. Students
will spend a minimum of 6 hours a week conducting lab research, working towards a
The second semester of the capstone experience continues with prototype design and
construction. Subsequently, students will perform testing of the solution and provide
an engineering and economic analysis of the solution. Students present the solution
at the end of the semester in the form of a presentation slide deck and pitch, as
if presenting to potential investors. Students will spend a minimum of 6 hours a week
working on prototype design and construction.
This course provides a comprehensive introduction to modern biomedical imaging modalities
that are currently employed in both biomedical research and clinical medicine. Imaging
modalities covered in this course include optical imaging, X-ray radiography, computed
tomography (CT), ultrasound, nuclear medicine (SPECT and PET), and magnetic resonance
imaging (MRI). The main objective is to offer students a solid understanding of each
imaging modality through lectures and assignments. For each imaging modality, we will
focus on basic physics, image formation and reconstruction, imaging hardware, and
applications. Image analysis and signal processing methods will also be briefly introduced.
The principles and practice of tissue engineering will be the focus of this course.
Topics include strategies for employing selected cells, biomaterial scaffolds, soluble
regulators of gene expression, role of stem cells, and mechanical loading and culture
conditions, Tissue fabrication techniques as well as the role of bioreactors in tissue
development will be explored. Students will investigate using current literature the
application of tissue engineering to specific organs.
This course covers theoretical foundations of biomedical optics, including light-tissue
interactions and optical imaging and sensing methods. Emphasis will be placed on skin
optics and photoacoustic phenomena. Students will perform computational modeling,
including Monte Carlo simulations of photon transport in turbid media.
This introductory course will cover fundamentals of micro/nanotechnology and its applications
in biomedical sciences. The course will provide rationale for utilizing micro/nanotechnology
for biomedical applications including scaling laws. Basic microfabrication methods
and design principles of microfluidics, lab-on-a-chip and microelectromechanical systems
(MEMS) used in biology and medicine will be presented. Students will gain a broad
perspective on applied research and commercial applications of biomedical microsystems.
This is an advanced course in the interdisciplinary field of biomedical microdevices.
This course will build upon a fundamental understanding of the principles of micro-
and nanoscale system design to explore state-of-the-art applications of biomedical
microdevices. Students will learn about the cutting-edge micro/nanofabrication techniques
and its most recent applications in biomedical sciences through in depth analysis
of recent publications.
This course addresses dynamic mathematical models of biochemical and genetic networks.
Emphasis on how modeling can enhance understanding of cell phenomena. Topics include
chemical reaction networks, biochemical kinetics, signal transduction pathways with
emphasis on receptor-mediated phenomena, metabolic networks, and gene regulatory networks.
Students will use current literature and programming to investigate specific models
and their predictive power for biological and tissue engineering applications.
Digital image processing is an indispensable component in biomedical research and
imaging. The goal of this course is to provide students a solid understanding of a
variety of image processing techniques and their implementations with a focus on biomedical
applications. Image processing methods will be introduced primarily using MATLAB.
Other image processing software, such as ImageJ and GIMP, will also be briefly introduced.
Knowing multiple image processing platforms offers students the freedom to choose
the most appropriate one to tackle specific image processing tasks. Topics of this
course include: image filtering in spatial- and frequency-domain, image restoration
and reconstruction, image transformation and registration, color image processing,
and morphological image processing.
Currently, the global medical device industry is valued at over $450B, with a CAGR
anticipated to be greater than 4%. In 2020 alone, the US FDA approved or cleared more
than 600 newly developed or modified medical and diagnostic devices for use. Today's
challenge is not only in gathering relevant regulatory information, but also in knowing
how to interpret and apply it. This course provides an overview of FDA and select
international regulations associated with medical devices, and those requirements
to be followed when submitting one for approval or clearance. Examples of topic areas
include: The Structure of the FDA and global approval agencies, Framework of regulatory
approvals, Classification of medical devices for approval, Relevant US and international
test methodologies, Guidance for conducting clinical trials, Good manufacturing practices
and quality systems to be adopted, and Surveillance of medical devices. Individuals
engaged in the development of medical devices and diagnostic tools, as well as those
in healthcare studies wishing to learn more about their evaluation and approval, would
benefit from information discussed in this course.
Assessment and modification of the physical environment to enhance occupational performance
including computer resources, assistive technology, home health, environmental controls,
and environmental accessibility.
This course is for research experience that includes engineering design and problem
solving in a biomedical engineering context.
This course is for external internships that cover design and engineering principles
in biomedical and biotechnology settings. This course will be supervised by a BME
With the guidance of a faculty member, a student within the Biomedical Engineering
Program may pursue an in-depth study of a subject area in an area of interest related
to their professional goals.