Board 32: Work in Progress: A New Approach to Student Learning of Real-time Biomedical Digital Signal Processing
- Conference
- Location
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Salt Lake City, Utah
- Publication Date
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June 23, 2018
- Start Date
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June 23, 2018
- End Date
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July 27, 2018
- Conference Session
- Tagged Division
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Biomedical Engineering
- Page Count
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7
- DOI
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10.18260/1-2--30009
- Permanent URL
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https://strategy.asee.org/30009
- Download Count
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834
Paper Authors
Willis J. Tompkins University of Wisconsin, Madison
Willis J. Tompkins received the B.S. and M.S. degrees in electrical engineering from the University of Maine at Orono in 1963 and 1965, respectively, and the Ph.D. degree in biomedical electronic engineering from the University of Pennsylvania in 1973. He is currently Professor Emeritus of Biomedical Engineering at the University of Wisconsin-Madison, where he was on the faculty from 1974 until he retired in 2014. He previously served for five years as Chair of the Department of Electrical and Computer Engineering. His teaching specialty is on the topic of computers in medicine, an area in which he has developed two courses. One of these two courses, he has evolved and taught for 40 consecutive years. He has received a number teaching awards including the University of Wisconsin Chancellor’s Award for Excellence in Teaching and the Theo C. Pilkington Outstanding Educator Award from the Biomedical Engineering Division of the ASEE. His research interests include development of microprocessor-based medical instrumentation, on-line biomedical computing, and real-time computer processing of electrocardiograms. Dr. Tompkins is a Life Fellow of the IEEE (Institute of Electrical and Electronics Engineers), a Founding Fellow of the AIMBE (American Institute for Medical and Biological Engineering), and an Inaugural Fellow of BMES (Biomedical Engineering Society). He is a past President of the IEEE EMBS (Engineering in Medicine and Biology Society) and a past Chair of the ASEE Biomedical Engineering Division.
Amit Janardhan Nimunkar University of Wisconsin, Madison
Amit J Nimunkar received his B.E. in Electronics Engineering from the University of Mumbai, India in 1999, M.S. in Bioengineering from the University of Toledo, Ohio in 2000 and Ph.D. in Biomedical Engineering from the University of Wisconsin-Madison, Wisconsin in 2009. He is currently the Associate Faculty Associate in Biomedical Engineering at the University of Wisconsin-Madison. His teaching specialty is on the topic of Biomedical Engineering Design and Bioinstrumentation and has taken initiative to develop hands-on blended learning based courses on the same topics. His research interest is on global health and engineering and currently working on projects in Honduras, Ethiopia, India and Vietnam. He has received the Recognition Award for Achievement in Global Engaged Scholarship in 2013 through the Wisconsin Without Borders at the University of Wisconsin-Madison, the Professor of the Year Award in 2012, through the Biomedical Engineering Society at the University of Wisconsin-Madison, and a number of teaching awards.
Abstract
We have revised the labs in our biomedical digital signal processing course to include real-time digital filter implementation using a compact microcontroller board. In the past, students only experienced the filter design process in lab using a unique MATLAB program we developed that provides a tool for designing digital filters and visualizing the filter results on a database of pre-sampled ECG signals. After designing the filters and obtaining their coefficients with this program, students now write C/C++ programs to implement filters on a powerful single-board microcontroller and process ECG signals in real-time. To support real-time signal processing, the microcontroller includes twelve 12-bit analog channels (up to 9 ADC and 3 DAC). Each student in the course purchases this microcontroller board (about $11.00 each). In two-student lab teams, one student’s microcontroller board runs an ECG simulator program we developed that provides a realistic real-time signal to the other student’s microcontroller board that the team programs with digital signal processing algorithms. Using keyboard input, students specify the heartrate, type of abnormality (e.g., periodic PVC’s), and type and amplitude of noise added to the signal including 60-Hz, EMG, and baseline drift. Students learn programming strategies for implementing FIR and IIR filters for ECG processing and ultimately implement a cascade of filters to achieve reliable real-time QRS detection on an inexpensive microcontroller appropriate for medical monitoring instrumentation. Students further test their real-time algorithms with their own ECGs as well as ECGs from on-line databases.
Tompkins, W. J., & Nimunkar, A. J. (2018, June), Board 32: Work in Progress: A New Approach to Student Learning of Real-time Biomedical Digital Signal Processing Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30009
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