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Fall 2025 Lecture Upper DivisionThis course uses real-world engineering problems to introduce advanced analytical tools and concepts relevant to biomedical engineering design. Each topic is briefly introduced, and students work in small teams to investigate physical mechanisms involving human anatomy and physiology using mathematical models and methods. Group work is done during scheduled class periods and other times by arrangement. Topics include brain concussions and protective helmets, origin of the electrocardiogram and bi-ventricular pacing, and deep brain stimulation for Parkinson's disease. Mathematical methods include coupled linear and nonlinear differential equations, finite element analysis, and simulated annealing. Creation of custom computer code is required. Students prepare extensive and detailed written technical reports. A midterm and a final examination encourage individual accountability and understanding.
Learning Outcomes1Accurately describe, with proper use and pronunciation of medical terms, the anatomy of a selected body organ or system, and a related disease process after independently conducting research using resources from various sources including the Internet.
2Create a useful biomechanical model of a body organ or tissue, describing the function of the body organ system in terms of algebra, calculus, and/or governing differential equations, evaluating constants in mathematical models on the basis standard normal physiology and routine medical observations.
3Write full length technical research progress reports and discuss the strengths and limitations of a particular mathematical model, with graphs and charts and a comprehensive bibliography of relevant research literature.
4Correctly solve equations, including second order, linear differential equations, and systems of equations, including coupled linear or nonlinear differential equations, by the method of undetermined coefficients, via programming in MATLAB or a suitable computational engine including the use of arrays and subroutines.
5Effectively work in diverse teams, both face-to-face and online, to enhance productivity and eliminate errors, while reconciling theoretical calculations with experimental observations and validating mathematical models by comparison with known analytical solutions.