Karen Payton, PhD
Professor
Electrical & Computer Engineering
Contact
508-999-8434
508-999-8489
kpayton@umassd.edu
Science & Engineering 214A
Education
| 1986 | Johns Hopkins University | PhD in Electrical Engineering |
| 1981 | Johns Hopkins University | MS in Electrical Engineering |
| 1977 | Carnegie Mellon University | BS in Electrical & Biomedical Engineering |
Teaching
Programs
Teaching
Courses
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
The first course covering basic theory of circuit analysis. The goals of this course include developing an ability to solve engineering problems and to design, implement and test circuits to meet design specifications. Topics include network theorems, review of techniques to solve simultaneous equations, nodal and mesh circuit analysis, dependent sources, Thevenin's and Norton's equivalent circuits, solution of first and second order networks to switched DC inputs, and natural responses. Group classroom and project activities require design, simulation, implementation and measurement of practical circuits. Written reports of project results are required.
The first course covering basic theory of circuit analysis. The goals of this course include developing an ability to solve engineering problems and to design, implement and test circuits to meet design specifications. Topics include network theorems, review of techniques to solve simultaneous equations, nodal and mesh circuit analysis, dependent sources, Thevenin's and Norton's equivalent circuits, solution of first and second order networks to switched DC inputs, and natural responses. Group classroom and project activities require design, simulation, implementation and measurement of practical circuits. Written reports of project results are required.
The second course in basic circuit theory and design. Topics include AC circuit steady-state response analysis, review of complex numbers, phasors, coupled inductors and ideal transformers, rms voltage and current, the maximum power transfer theorem, balanced 3-phase systems, and power and energy computations, applications of Laplace transforms to solutions of switched circuits and differential equations with initial conditions, stability, poles/zeros, Fourier transform, frequency response, Bode plots, network analysis, and equivalent circuits. Students are introduced to graphical convolution and Fourier series. Group classroom and project activities require design, implementation and measurement of filters and other circuits to meet design specifications.
The second course in basic circuit theory and design. Topics include AC circuit steady-state response analysis, review of complex numbers, phasors, coupled inductors and ideal transformers, rms voltage and current, the maximum power transfer theorem, balanced 3-phase systems, and power and energy computations, applications of Laplace transforms to solutions of switched circuits and differential equations with initial conditions, stability, poles/zeros, Fourier transform, frequency response, Bode plots, network analysis, and equivalent circuits. Students are introduced to graphical convolution and Fourier series. Group classroom and project activities require design, implementation and measurement of filters and other circuits to meet design specifications.
Research
Research Interests
- Auditory perception
- Digital signal processing
- Speech acoustics
- Speech processing
Dr. Karen L. Payton is Professor of Electrical and Computer Engineering at the University of Massachusetts Dartmouth and holds a Visiting Scientist position with the Research Laboratory of Electronics at MIT.
She received her B.S. degree as a double major in Electrical and Biomedical Engineering from Carnegie Mellon University. She earned her M.S. and Ph.D. degrees in Electrical Engineering at the Johns Hopkins University.
Dr. Payton is actively involved in research in the area of digital signal processing, as applied to predicting the intelligibility of speech degraded by room acoustics and/or reduced capabilities of a listener. She has also investigated processing capabilities of the auditory system through comparisons of computer simulations of peripheral auditory processing with physiological data.
She is a member of the Acoustical Society of America, the Institute of Electrical and Electronic Engineers, the Society of Women Engineers, and the American Society for Engineering Education.