Bioengineering 316 --- Bioechemical Signals and Sensors
Instructor: Christopher Neils
cmneils@u.washington.edu
Credits: 3
UW General Catalog Course Description:
Introduction to the sources, detection, and processing of signals in medical instrumentation. Analog and digital signal processing in the time and frequency domains. Emphasizes component strengths and limitations, to develop systems that improve safety, accuracy and reliability.
Prerequisites:
AMATH 301, PHYS 122. Corequisite: Either MATH 307 or AMATH 351. Requires concurrent registration with BIOEN 317.
Overview:
This course introduces the acquisition, processing, and interpretation of biological and medically relevant signals. The course sequence begins with the user and display interface, then moves backward along the signal flow path to finish with details of various biological sensor types. This sequence recognizes that the student is more interested in the output of the diagnostic system than in the ouput of the transducers or filters per se. In addition, each stage in the signal flow path provides the motivation for the preceding stage. For example, display systems often require sophisticated digital signal processing, and digitization requires prior analog filtering and amplification. Therefore, the first half of the course introduces techniques to analyze and implement analog and digital frequency filters, operational amplifiers, and signal sampling. By the time students reach the sensors part of the course, they have the conceptual tools to relate what the user sees on the front panel to the signal captured at the sensor. Biomedical sensor technology is treated in depth in the second half of the course, drawing on content in the concurrent Biochemical and Molecular Bioengineering course. Sensor topics include surface and implantable electrodes, photometry, biochemical sensors, force and position detectors, piezoelectric devices, life science microscopes, and surface plasmon resonance. Throughout the course, emphasis is placed on recognizing and accommodating limitations inherent in sensor and signal processing systems.
Textbooks:
1) Medical Instrumentation: Application and Design, by John G. Webster. 4th Edition, © 2010.
2) Electric Circuits, by James Nilsson and A. Riedel, 8th edition, 2008
or
Signals and Systems Analysis in Biomedical Engineering, by Robert B. Northrop, 2003.
Learning Objectives:
Students will learn the following fundamental concepts:
Characteristics, basis and utility of a variety of biomedical signals;
Frequency domain analysis via Fourier transforms;
Limitations of signal sampling;
Basic principles of biosignal transduction;
Characteristics, limitations, and applications of a variety of signal transducers;
Biosignal and medical device terminology.
Students will also develop the following skills:
Application of time-frequency transformations and interpretation of the results;
Selection and implementation of simple digital and analog frequency filters;
Implementation of simple signal acquisition routines using MATLAB or LabView.
Course Grading:
| 10 Homework exercises | 20% | To practice mathematical concepts |
| 5 Problem sets | 25% | Programming tasks, device analysis, and design |
| Sensor presentation | 10% | Submitted online as a video |
| 2 mid-term quizzes | 20% | #1 on Fourier transforms; #2 on RLC filters and op-amps |
| Final exam | 25% | Comprehensive |
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