Tompkins, Willis J.

J. Pan and W. J. Tompkins, A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng., BME-32 (3):230-236, 1985.
P. S. Hamilton and W. J. Tompkins, Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database, IEEE Trans. Biomed. Eng., BME-33(12):1157-1165, 1986.
P. S. Hamilton and W. J. Tompkins, Compression of the ambulatory ECG by average beat subtraction and residual differencing, IEEE Trans. Biomed. Eng., BME-38 (3): 253–259, 1991.
P. S. Hamilton and W. J. Tompkins, Theoretical and experimental rate distortion performance in compression of ambulatory ECG’s, IEEE Trans. Biomed. Eng., BME-38(3): 260–266, 1991.
Q. Xue, Y. H. Hu, and W. J. Tompkins, Neural-network- based adaptive matched filtering for QRS detection, IEEE Trans. Biomed. Eng., BME-39(4): 317–329, 1992.
W. J. Tompkins (ed.) Biomedical Digital Signal Processing: C Language Examples and Laboratory Experiments for the IBM PC. Englewood Cliffs, NJ: Prentice Hall, 1993.
Y. H. Hu, W. J. Tompkins, J. L. Urrusti, and V. X. Afonso, Applications of artificial neural networks for ECG signal detection and classification, Journal of Electrocardiology, 26 (suppl): 66–73, 1994.
V. X. Afonso and W. J. Tompkins, Detecting ventricular fibrillation, IEEE Engineering in Medicine and Biology Magazine, 14(2): 152–159, 1995.
V. X. Afonso, W. J. Tompkins, T. Q. Nguyen, K. Michler, and S. Luo, Comparing stress ECG enhancement algorithms: With an introduction to a filter bank based approach, IEEE Engineering in Medicine and Biology Magazine, 15(3): 37–44, 1996.
S. Palreddy, Y. H. Hu, and W. J. Tompkins, A patient-adaptable ECG beat classifier using a mixture of experts approach, IEEE Trans. Biomed. Eng., BME-44(9): 891 900, 1997.
V. X. Afonso, W. J. Tompkins, T. Q. Nguyen, and S. Luo, ECG beat detection using filter banks, IEEE Trans. Biomed. Eng., BME-46(2): 192-202, 1999.
Publications on File with the National Library of Medicine

Selected Awards, Honors and Societies

Distinguished Engineering and Technology Award from the University of Maine, 1989
Life Fellow of the IEEE (Institute of Electrical and Electronics Engineers), 1992
Fellow of the Biomedical Engineering Society, 2005
Fellow of the AIMBE (American Institute for Medical and Biological Engineering), 1992
Outstanding ECE Instructor, Polygon Engineering Council, University of Wisconsin, 1993
Honorary member of Kappa Eta Kappa electrical engineering fraternity, 1993
Centennial Certificate, American Society for Engineering Education (ASEE), 1993
Chancellor's Award for Excellence in Teaching, University of Wisconsin, 1994
Theo C. Pilkington Outstanding Educator Award, Biomedical Engineering Division of the ASEE, 1995
Benjamin Smith Reynolds Award for Excellence in Teaching Engineers, College of Engineering, University of Wisconsin, 1997
IEEE Millennium Medal, 2000
Outstanding Biomedical Engineering Instructor, Polygon Engineering Council, University of Wisconsin, 2001 and 2002
EMBS Career Achievement Award, IEEE Engineering in Medicine and Biology Society, 2002

Summary

The medical environment is characterized by many instruments that include embedded microcomputers. The natural evolution of the microcomputer-based instrument has been toward more intelligent devices. These instruments are involved in both monitoring and therapy of patients and typically must operate in real time. For example, an intensive care unit computer must acquire a patient's electrocardiogram, recognize key features of the signal, determine if the signal is normal or abnormal, and report this information in a timely manner.

My principal interests involve software design of the requisite real-time biomedical digital signal processing algorithms required in such devices, particularly for electrocardiogram analysis.

Files and Links of Interest

ANN for ECG analysis paper: Y. H. Hu, W. J. Tompkins, J. L. Urrusti, and V. X. Afonso, Applications of artificial neural networks for ECG signal detection and classification, Journal of Electrocardiology, 26�(suppl): 66�73, 1994.
Biology in Engineering Certificate Program
CV - Willis Tompkins
ECG analysis paper: P. S. Hamilton and W. J. Tompkins, Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database, IEEE Trans. Biomed. Eng., BME-33(12):1157-1165, 1986.
Parkinson's laser cane presentation
QRS Detector Paper Errata
QRS Detector paper: J. Pan and W. J. Tompkins, A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng., BME-32(3):230-236, 1985.
Undergraduate degree program

Copyright 2008 The Board of Regents of the University of Wisconsin System
Date last modified: 19-Jun-2008
Content by: tompkins@engr.wisc.edu
Accessibility

Web services
Thank you for visiting http://www.engr.wisc.edu/bme/faculty/tompkins_willis.html

UPDATE PROFILE