Courses Taught by Patrick M. Boyle
BIOEN 400: Fundamentals of Bioengineering Design
Description: This project-based course exposes undergraduates to the design process and incorporates modern tools and methodologies for developing innovative health technologies. It is structured around a team project in which students strategically craft a plan to carry out a successful exercise in bioengineering design. Students engage in critical design review of their technological solution, culminating in a term presentation during which they describe their plan to the class. Emphasis is placed on designing for social responsibility and healthcare equity.
Learning Objectives: (1) Implement the engineering design process to develop health technologies subject to technical constraints; (2) Assess designs for realistic constraints; (3) Use technical communication to document design; (4) Enhance effective teamwork skills, including fostering an inclusive environment; (5) Implement statistics to manage multivariable inputs using design of experiments; and, (6) Reinforce knowledge from other classes to conceive and evaluate design solutions through engineering analysis.
BIOEN 498/599: Computational Modeling & Simulation of Bioelectricity
Note: Pending UW approval, this course will soon be renumbered as 484/584
Description: This course explores quantitative modeling and simulation of electrically excitable cells, with a focus on cardiac electrophysiology. Topics include ion channel gating kinetics, bioelectric propagation, and nonlinear dynamics underlying cardiac arrhythmia.
Learning Objectives: (1) Understand and apply quantitative descriptions of bioelectricity generation; (2) Recognize equivalent circuit representations of excitable biological tissue; (3) Implement and analyze cell- and tissue simulations of electrically excitable mammalian tissue; (4) Explain the biophysical basis of signals recorded non-invasively (e.g., body surface potentials in the ECG); (5) Describe factors underlying arrhythmia; and, (6) Assess reproducibility and model credibility for published computational cardiac electrophysiology studies.