This course introduces basic computational problem solving techniques used in engineering. Topics include: 1) Use of common engineering tools (Excel, Matlab) to analyze data, 2) Development of algorithms and flowcharts to solve engineering problems, 3) Application of basic programming concepts (input/output methods, variable types, repetition structures, decision structures, and subprograms) to create user-friendly computer programs (VBA, Matlab) that perform complex engineering calculations.

Numerical techniques necessary for engineering analysis are introduced that build upon concepts from core mathematics and engineering courses. Mathematical problems naturally arising in biomedical engineering are used to motivate the course topics and techniques taught. Tools such as MATLAB and Excel spreadsheets are used to implement numerical methods and examine data results. Topics include root-finding techniques for nonlinear equations, curve fitting using linear regression techniques, methods for solving systems of linear equations, numerical differentiation and integration methods, optimization techniques, and methods for reducing numerical error.

This is the first in a two-course sequence oriented to the solution of real-world engineering design problems. This is a capstone learning experience that integrates engineering theory, principles, and processes within a collaborative environment. Multidisciplinary student teams follow a systems engineering design process, which includes assessing customer needs, developing engineering specifications, generating and evaluating concepts, choosing an approach, developing the details of the design, and implementing the design to the extent feasible, for example by building and testing a prototype or implementing a chosen set of improvements to a process. This first course focuses primarily on defining the problem and developing the design, but may include elements of build/ implementation. The second course may include elements of design, but focuses on build/implementation and communicating information about the final design.

This is the second in a two-course sequence oriented to the solution of real-world engineering design problems. This is a capstone learning experience that integrates engineering theory, principles, and processes within a collaborative environment. Multidisciplinary student teams follow a systems engineering design process, which includes assessing customer needs, developing engineering specifications, generating and evaluating concepts, choosing an approach, developing the details of the design, and implementing the design to the extent feasible, for example by building and testing a prototype or implementing a chosen set of improvements to a process. The first course focuses primarily on defining the problem and developing the design, but may include elements of build/ implementation. This second course may include elements of design, but focuses on build/implementation and communicating information about the final design.

One semester of paid work experience in biomedical engineering.

Modeling and simulation is an important tool in the medical field and is commonly used to facilitate equipment design, control of devices, research, and training. This course will focus on analytical techniques needed for creating complex simulation models. Models will be developed which use mathematics, physics and engineering principles to describe human physiologic behavior in order to demonstrate the practical application of the theory.

Allows graduate students an opportunity to independently investigate, under faculty supervision, aspects of the field of biomedical engineering that are not sufficiently covered in existing courses. Proposals for independent study activities must be approved by both the faculty member supervising and the graduate program director.