Asee peer logo

Integration of a Computational Lab Sequence Into a Junior-level Quantitative Physiology Course

Download Paper |


2012 ASEE Annual Conference & Exposition


San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012



Conference Session

BME Course and Curriculum Development

Tagged Division


Page Count


Page Numbers

25.816.1 - 25.816.10



Permanent URL

Download Count


Request a correction

Paper Authors


Kurt A. Thoroughman Ph.D. Washington University, St. Louis

visit author page

Kurt A. Thoroughman, Ph.D., is the Associate Chair for Undergraduate Studies and an Associate Professor in the Department of Biomedical Engineering at Washington University in St. Louis. Thoroughman has joint appointments in the departments of Anatomy & Neurophysiology and Physical Therapy.

visit author page


Ranjan Patrick Khan Washington University, St. Louis

author page

Haoxin Sun Washington University, St. Louis


Patricia L. Widder Washington University, St. Louis

visit author page

Patricia Widder serves as Teaching Lab Coordinator in the Biomedical Engineering Department at Washington University in St. Louis. She received her B.S. degree in electrical engineering from the University of Illinois, Urbana-Champaign, and her M.S. degree in biomedical engineering from Washington University in St. Louis. Prior to her current position, she worked as an instrumentation and controls engineer for Monsanto, Co.

visit author page

Download Paper |


Integration of a Computational Lab Sequence Into a Junior-Level Quantitative Physiology CourseQuantitative Physiology I is a junior-level course that requires students to integrate overfoundational coursework in physics, biology, electrical and mechanical engineering, computerscience, and technical writing. Students explore current and classic models of instrumentation,nerve, muscle, and biomechanics. Preceding 2004 the course was three credits consisted of alecture- or lab-format; each week featured either traditional lectures or hands-on dry or wetlaboratories. A consequence of the either-or structure was gap generation in lecture, leading tolack of substance and theme continuity, and a lack of thought or energy preceding or followinglabs. A consequence of that structure was a lack of continuity in substance and theme of thecourse.In 2005 we expanded the course to four units and added a computational lab sequence. Theselabs were designed with several goals: - theoretical and numerical exploration of core concepts introduced in lecture - substantive preparation for ideas underlying physical labs - overall investigation and appreciation of the dynamic nature of models, above and beyond what is possible with pencil and paper - integration across the course to discover mathematical and quantitative physiological concepts that spanned individual topics and modulesStudents completed computational labs in three to four hour sessions, using Simulink as adynamic programming platform and MATLAB to drive simulations and analyze outputs.Individual labs considered elementary physical systems; simple filters and feedback systems;retinal processing; resistor-circuit models of excitable tissue; Hodgkin-Huxley formalism ofaction potential generation; and isometric and isotonic force generation of a Hill-type musclemodel. Students submitted informal lab reports that summarize model output, subsequentanalyses, and text demonstrating their understanding of the simulation and its relevance to corecourse concepts.The final computational lab session was a practicum examination. Students were given a newphysiological problem and required to build a model, analyze the results, and report insightgained from modeling. An example practicum problem was the simulation of a stretch reflex,which required explicit integration over prior sessions.This paper demonstrates two outcomes achieved by our seven years of teaching thecomputational lab sequence: the ability of students to integrate concepts from across the course,as evidenced by their computational lab reports, and the ability to generalize beyond theircomputational training, as evidenced by computational lab practicum performance.

Thoroughman, K. A., & Khan, R. P., & Sun, H., & Widder, P. L. (2012, June), Integration of a Computational Lab Sequence Into a Junior-level Quantitative Physiology Course Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21573

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2012 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015