2024-2025 Academic Catalog
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
In September 2018, the State Council of Higher Education for Virginia approved a new undergraduate degree program in Biomedical Engineering (BME) at Virginia Tech, housed within the Department of Biomedical Engineering and Mechanics (BEAM). Unlike other BME programs, Virginia Tech's program has an extensive foundation in fundamental engineering principles. This approach means students will gain a more comprehensive understanding of broader engineering practice and cross-disciplinary teambuilding. The goal is that graduating engineers can be fully integrated into diverse health care teams in order to better respond to industry needs. Graduates will be primed for placement in such fields as telemedicine, health care, data analytics, personalized medicine, medical robotics, and biomedical device design and regulatory practices, among others.
The foundation in mechanics combined with a total of 21 technical elective credits give students the flexibility to tailor their undergraduate degree within subdisciplines of the vast field of biomedical engineering. Our faculty expertise ranges from biomechanics, biomaterials, biomedical imaging, cardiovascular engineering, neuroengineering, tissue engineering, translational cancer research, and more. Additionally, our curriculum emphasizes active learning strategies and "hands-on" learning experiences to promote engaged learning and development of communication, teamwork, critical thinking, and problem-solving skills. There are also numerous opportunities to participate in design experiences throughout the curriculum, culminating in the senior capstone sequence that includes consideration of design controls and regulatory processes. The BEAM department also offers a Minor in Biomedical Engineering for undergraduate students.
The BEAM department also participates in the Accelerated Undergraduate / Graduate Degree Program, in which students meeting the requirements for the program apply for admission to the Graduate School during their junior year. This program allows students to enroll and "double-count" 12 credit hours of graduate coursework taken during their senior year of their undergraduate program at VT. The graduate program in BME is a joint program between the Virginia Tech College of Engineering and the Wake Forest School of Medicine to form the Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences (SBES) program. The SBES program is a unique multidisciplinary joint program that bridges the biomedical sciences and BME towards translational, real-world applications, offering MS, PhD and DVM/PhD at the VT campus.
The Biomedical Engineering program is accredited by the Engineering Accreditation Commission of ABET, https://www.abet.org, under the commission’s General Criteria and the Program Criteria for Bioengineering and Biomedical and Similarly Named Engineering Programs.
Biomedical Engineering is a multidisciplinary field, using engineering principles and design concepts to advance healthcare treatment and find innovative solutions. We strive to prepare our graduates to succeed in advanced graduate or professional study, industry, and government. Within a few years after graduation, we expect our graduates to productively contribute to improving the human condition. In these activities, our alumni will attain the following program educational objectives within a few years following graduation:
These program educational objectives are supported by a curriculum that seeks to have its graduates achieve the following student learning outcomes by the time they graduate:
Department Head: Stefan Duma
Undergraduate BME Program Chair: Sara Arena
N. Waldo Harrison Professor: P. VandeVord
Newport News-Tenneco Professor: T. Dingus
L. Preston Wade Professor: R.M. Queen
Harry C. Wyatt Professor: S.M. Duma
Professors: T. Dingus, S.M. Duma, R. Gourdie, S. LaConte, S.H. McKnight, J. Munson, S. Poelzing, R.M. Queen, and P. VandeVord
Associate Professors: J. Chappell, Z. Doerzaph, Y.W. Lee, M. Perez, S. Rowson, C.D. Untaroiu, E. Vlaisavljevich, and V.M. Wang
Assistant Professors: C. Collins, N. Gurari, A. Han, O. Kim, A Korneva, and M. Roberts
Collegiate Associate Professors: C. Arena and S. Arena
Collegiate Assistant Professors: A. Taylor
Instructors: K. Tate and J. Newton
Professor of Practice: A. Muelenaer and R. Stone
Affiliate Faculty: Over 150 affiliate faculty (https://beam.vt.edu/people/faculty.html)
Academic and Career Advisor: A. Sandridge
Broad, multidisciplinary description of concussion as it relates to variety of fields including: medicine, psychology, injury biomechanics, technology, equipment design, ethics, and law. Concussion modeling, animal models, diagnosis, neurocognitive testing, and treatment. Testing and instrumentation. Research efforts, credibility and conflicts of interest. Ethical considerations in sports, medicine, and science. Legal implications.
Topics selected to foster professional development of the Biomedical Engineering (BME) student, including training for experiential learning opportunities, such as research, internships, co-ops, and design. Overview of BME specialization and research areas, career pathways, and preparation for interactions with industry, including the regulatory approval process associated with medical device development. Emphasis on teamwork, communication, employment opportunities, the development of a professional portfolio, ethical considerations, additive manufacturing, and engineering documentation using real-world examples and a design sprint/challenges.
Professional development seminar series for National Institutes of Health (NIH) Enhancing Science, Technology, EnginEering, and Math Educational Diversity (ESTEEMED) program scholars. Professional development and construction of professional portfolio. Overview of safety and ethical considerations within biomedical engineering research. Development of scientific literature searching and summarizing skills. Communication skill development of written and oral content. Strategies for mentoring relationships. May be repeated 3 times with different content for a maximum of 4 credit hours. Pre: Only available to students in the ESTEEMED program.
Numerical methods and software applied to biomedical engineering applications. Structured programming and problem solving within programming environment such as MATLAB. Error estimation, root finding, curve fitting, interpolation, solving linear simultaneous equations, numerical differentiation, numerical integration, and numerical solutions to ordinary differential equations.
Identification, exploration, and evaluation of real-world, complex biomedical engineering problems including safety and ethical considerations. Emphasis on critical thinking, problem solving, group skills, and communication related to the field of biomedical engineering. Literature review and experimental design in biomedical engineering research.
Provides a multidisciplinary description of helmet design with applications to all sports. The biomechanical design parameters for helmets are presented in the broader context of health and social disparities. Through reasoning in the social sciences the class investigates how sex and gender roles have shaped sports and their individual helmet design disparities. A critical analysis of equity relative to race and healthcare is analyzed as it pertains to helmets and concussion treatments and outcomes. Demonstrate the interdisciplinary nature of helmet design and how ethical reasoning and social constructs have shaped the industry.
Principles of cell engineering, experiment design, quantitative alyses. Laboratory notebook keeping, report writing and oral presentation in a team setting. Measurement of biological molecules such as DNA, RNA, and proteins. Assessment of animal cell viability, migration, mechanics and interactions with biomaterials. Identification of cell phenotypes.
Principles of biomedical sensors and their usage for experimental design. Collection of biological signals using analog signal amplifiication and filters, biopotentials, digital acquisition, digital filtering and processing. Analysis of physiological signals on living systems with focus on neural, cadiovascular, respiratory, and muscular systems using a group problem solving approach. Instrumental regulation and safety considerations.
Define open-ended problem statements related to healthcare. Immersive clinical observation and transdisciplinary medical technology innovation. Needs exploration and screening, disease state fundamentals, and evaluation of existing solutions. User-centered research planning, contextual inquiry, data documentation, stakeholder and market analysis, and regulatory and reimbursement basics.
Basic principles of biomechanics. Basic musculoskeletal anatomy. Application of classical mechanics to biological systems. Emphasis placed on mechanical behavior (stress and strain), structural behavior, motion, and injury tolerance of the human body. Biomechanics of medical devices and implants. Advances in safety equipment used in automotive, military, and sports applications.
Introduction to major biomedical imaging modalities. Emphasis on X-rays, computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), ultrasound, and optical imaging. Essential physics and imaging equations of the imaging system. Sources of noise and primary artifacts. Patient safety and clinical application.
Design and uses of biomedical devices for diagnosis and therapy of human and animal diseases. Disease eiologies, progression, risk factors, and epidemiology. Tissue, organ, and systems dysfunction and failure and relevance to life stages (pediatric, adolescent, adult, aged). Useful characteristics of engineered materials for device fabrication, including biocompatibility. Gaps between medical needs and current medical devices.
Introduction to the concepts and applications of digital signal processing and machine learning on bioinstrumentation signals from physiologic systems. Emphasis on processing techniques for electrocardiogram (ECG), electromyography (EMG), and speech signals. Apply basic machine learning algorithms for diagnostic classification of biosignals.
Fundamentals of cell biology, physiology, and engineering of regenerative medicine. Techniques and technologies of regenerative medicine and tissue engineering. Biomaterial selection and manufacturing techniques for regenerative medicine and tissue engineering applications. Overview of genetic and immuno- therapies. Design criteria and process from bench to clinical implementation of tissue engineering solutions. Ethical implications in regenerative medicine.
Computational and analytical approaches to analyzing biological systems and solving biomedical engineering problems. Problem formulation and exploration of problem-solving techniques to validate computational solutions. Self-directed inquiry and team-based approaches that use reverse engineering, user-in-mind design, and engineering software tools.
Provides multidisciplinary analysis of automobile safety around the world. Illustration of the details about the invention of the wheel and how various cultures advanced the wheel into carts for transportation. Design process of seatbelt systems, frontal airbag and side airbag systems. Analysis of vehicle design parameters to optimize restraint systems. Analysis of the design challenges of protecting all occupants including men, women, children, elderly and pregnant occupants. Ethical analysis of the history of laws, media, and societal norms around seatbelt use and current distracted drivers using cell phones.
Introduction to computational and systems neuroscience. Data analysis and signal processing techniques for neural data. Neural modeling to include mean field models, Hodgkin-Huxley models, integrate and fire models. Neural engineering and brain machine interface (BMI) applications.
Application of academic knowledge and skills to in a work-based experience aligned with post-graduation goals using research-based learning processes. Satisfactory completion of work-based experience often in the form of internship, undergraduate research, co-op, or study abroad; self-evaluation; reflection; and showcase of learning. Pre: Departmental approval of 3900 plan.
4015: Apply biomedical engineering principles to the design of an approved project using the team approach. Develop design and communication skills. Integrate ethical, global and social issues in engineering. 4016: Apply biomedical engineering principles to develop solutions for an approved design project using a team approach. Complete a project resulting in prototype medical device, circuit, or system. Refine design and communication. Integrate ethical, global, environmental and social issues in engineering. Pre: Senior standing for 4015.
4015: Apply biomedical engineering principles to the design of an approved project using the team approach. Develop design and communication skills. Integrate ethical, global and social issues in engineering. 4016: Apply biomedical engineering principles to develop solutions for an approved design project using a team approach. Complete a project resulting in prototype medical device, circuit, or system. Refine design and communication. Integrate ethical, global, environmental and social issues in engineering. Pre: Senior standing for 4015.
Exploration of science, engineering, and data analytics principles behind wearable technology. Non-invasive measurement and assessment of human physiology and behavior. Data processing and analysis of non-invasive biosignals. Data privacy, protection, and ethical considerations of wearable devices.
An introductory to the principles of medical physiology. Designed primarily for (but not limited to), undergraduate students minoring in biomedical engineering, and other related engineering and physical sciences majors with little or no formal background in biological sciences. Basic principles and concepts of human physiology. Special emphasis on the interactions of human systems biology in their entirety rather than individual genes and pathways. Pre: Junior standing or permission of instructor.
Overview of contemporary technological advances to improving human health. Comparison of healthcare systems, problems, and existing solutions throughout the developed and developing world. Consideration of legal and ethical issues associated with developing and implementing new medical technologies. Recognition and definition of gaps between medical needs and current methods and therapies between developed and developing countries. Conceptually design a novel technology.
Commercialization process applied to translational research. Regulatory aspects of biomedical engineering products and technologies (e.g. devices, diagnostics, drugs, biologics). Intellectual property, technology transfer processes, clinical trial design, commercialization of university research, modeling of development costs (e.g. cash flow and revenue projections). Small business startup approaches.
Anatomy and physiology of biological systems such as cells, tissues, and organs. Experimental techniques for determining the mechanical behavior of biological systems. Simplified mechanics-based mathematical models of biological systems. Specific biological systems include cells, tissues, and organs of the musculoskeletal, cardiovascular, integumentary system, and reproductive systems.
Materials for biomedical applications. Basic material types and properties, functional uses of materials in medical applications, and tissue response mechanisms. Integrated design issues of multicomponent material design in prosthetic devices for hard and soft tissues, orthopedics , cardiovascular, and drug delivery applications.
Uncertainty analysis of engineering data, parameters estimation, probability concepts, random variables, functions of random variables, probability-based performance functions and failure modes, risk and reliability functions, probability of failure and safety index, random sequences and stochastic processes, correlation functions and spectral densities, return period and extreme values, failure rates, performance monitoring and service life prediction.
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