Course: BIOEN 316: Biomedical Signals and Sensors

Credits: 3

Instructor: Chris Neils

Texts and Supplemental Materials: Circuits, Signals and Systems for Bioengineers, J. Semmlow, 2nd edition.

UW Catalog Description: Introduces the sources, detection, and processing of signals in medical instrumentation. Includes 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.

Instructor Course Description: This course introduces the acquisition, processing, and interpretation of biological and medically relevant signals. The course sequence begins with the user and display interface, and then moves backward along the signal flow path to finish with details of various biological sensor types. This sequence recognizes that a user is more interested in the output of the diagnostic system than in the output of the transducers and circuitry that compose it. 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 may 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.

Prerequisites by Course: Prerequisite: AMATH 301 and PHYS 122; BIOEN 317, which must be taken concurrently; either MATH 307 or AMATH 351, which may be taken concurrently.

Prerequisites by Topic: Introductory MATLAB programming, Introduction to computational solutions of ODEs and PDEs, Introductory Electromagnetism, Mechanics (oscillators). Corequisite: Differential equations.

Required or Elective: Required

Course Structure: BIOEN 316 employs lectures, practice problems, homework problems, and bi‐weekly quizzes.

Lectures: There are three 1‐hour lectures per week. No points are awarded or deducted for attendance in lecture. However, students are expected to have attended the relevant lecture(s), or at least have reviewed the relevant material, before coming to office hours with questions.

Pre‐lecture reading assignments may be given for days when there is no quiz or homework due. For some of the material, a Catalyst survey will be used as an incentive. This will be new material, so naturally you will not be expected to understand the more complicated concepts. Nonetheless, the instructor will assume that you have done the reading, and you might be called on to explain what you have read or at least to ask relevant questions.

Labs: BIOEN 316 does not have an integrated lab. However, because many of the concepts and procedures are most effectively learned through practice with individualized help, the BIOEN 317 Signals and Sensors Lab course is a required adjunct to BIOEN 316.

Homework: There will be approximately one homework per week. As much as practical, the homework will be due on Fridays. When there is a known conflict with another activity (e.g. a midterm in BIOEN 315), the homework due date will be moved. Homework assignments will be due either at the beginning of lecture OR will be submitted on line, depending on the nature of the assignment. Homework turned in late but before solutions are posted may be penalized at 5% per day unless prior arrangements have been made. No points are awarded for homework turned in after solutions are posted, but we will be glad to read and correct the homework no matter how late (within reason). If you cannot turn in an assignment due to illness, please let the instructors know and we might postpone the solution posting date. Students may discuss the problems, solution strategies and MATLAB syntax, but then are expected to produce their own code and report. Similar to the policy in Computer Science, no matter how you got there, by the time you do the assignment you should understand what you did and how to do it again.

The BIOEN 315 and 316 instructors will, as much as possible, avoid scheduling tests during the same week, and major assignments on the same day. Exams or reports in non-bioengineering courses will be considered but are not generally reason enough to change the BIOEN 316 schedule.

Quizzes: There will be four or five 20‐minute quizzes, each of which will be based on a set of practice problems. If you can do the practice problems, you will probably be able to do the quiz. None of these practice problems needs to be turned in. You are welcome to use any resources, such as cramster.com, to help you understand the solutions to these practice problems. If an in‐class quiz must be missed, the instructor should be notified beforehand so arrangements can be made. If a fifth quiz is given, the lowest score will be dropped.

Exams: The final exam will be comprehensive and may include material from the quizzes, homework, and lectures. There will be no midterm exam other than the quizzes.

Computer Use: Homework problems use MATLAB (including Signal Processing Toolbox) for digital filter design and implementation, Excel for signal plotting and statistical analysis, and PSPICE or equivalent to simulate analog circuit behavior. Completion of reading assignments will be tested via brief Catalyst surveys.

Grading distribution:
Homework 32% [Simple practice exercises plus longer problem sets]
Special project 08% [Essay or video on contemporary issues or sensor design]
4 mid‐term quizzes 32% [25 minutes each]
Final exam 28% [Comprehensive]

It is traditional in my courses that the final percentage is mapped onto the 4.0 scale, such that 25% would become 1.0 and 75% would be 3.0. All grades are then scaled such that the highest‐performing student receives a 4.0.

 Topics Covered

  1. Types of medical instruments, sources of biomedical signals.
  2. Signal sampling, aliasing, and noise.
  3. Fourier series and the frequency domain.
  4. Discrete Fourier transforms, digital signal filtering, including finite impulse response filters, convolution, and infinite impulse response filters.
  5. Operational and instrumentation amplifiers.
  6. Analog filtering, including sensor‐circuit interface, impedance, and noise.
  7. Photometric, thermal, bioelectric, biomechanical and biochemical sensors, strain gauges and bridge circuits.
  8. Ultrasonic transduction.
  9. Device fabrication.
  10. Electrical safety.

 Specific Outcomes:

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.

Outcomes Addressed by this Course:

A. An ability to apply knowledge of mathematics, science, and engineering.

  • Apply digital signal processing theory to signal analysis and filtering; analyze and design analog circuits for signal filtering and amplification.

Concepts and techniques are presented in lecture, practiced in homework, explored in lab, and reinforced with biweekly quizzes. Student competency is assessed primarily with a final exam question, worth 5‐10% of the course grade, that asks students to outline a system to acquire and display a given surface biopotential or optically acquired signal.

 L. An understanding of biology and physiology.

  • Describe sources of electrophysiological signals and the instrumentation used to measure these signals.

Lectures and readings will include explanations of muscle fiber contraction as the source of the EMG, cardiac physiology as the source of the ECG, anatomical interfaces as the reflecting features in ultrasound imaging, and arterial pulsations as the basis for pulse oximetry. Student knowledge will be developed through homework assignments and assessed via a final exam question that will be worth ~5% of the course grade. A typical question would ask students to illustrate conduction pathways through the heart, describe briefly how neuromuscular signals produce a measurable ECG, and describe a few pathologies that can be detected using an ECG.

 M. An ability to apply advanced mathematics, science, and engineering (including differential equations and statistics) to solve problems at the interface of engineering and biology.

  • Design analog circuits for signal filtering and amplification; analyze these circuits using differential equations and complex frequency-domain methods and Fourier transforms.

Examples in lecture and homework are framed around biomedical measurements, so students relate the biomedical need for the measurement with the applied formulas and the performed calculations. Concepts are reinforced in bi‐weekly problem sets. Achievement will be assessed via a midterm quiz or final exam questions, worth 5‐10% of the course grade, that asks students to design and analyze electronic circuits that are appropriate for a given biological signal and output function.

 N. An ability to make measurements on and interpret data from living systems, addressing the problems associated with the interaction between living and non-living materials and systems.

  • Identify ways that sensors interact with biological systems and the resulting effects on biological measurements. Identify ways to minimize problematic interaction of biological sensors and measurements.

Student knowledge will be developed through lectures and a written assignment that address the following:  (1) considerations for external and internal measurements, such as motion artifact for surface biopotentials, injury or infection from invasive devices, and encapsulation of implantable devices, (2) ways to improve the quality of information obtained, for example by surface treatment of implantable devices, or signal processing to remove artifacts, and (3) ways to decrease invasiveness, such as optical instruments, and increased lifetime of implantable devices to reduce surgical frequency. Student knowledge will be assessed via a final exam question, worth ~5% of the course grade, that asks students to explain one or more methods that have been used in the past to minimize the impact of biofouling, to improve patient electrical safety, to reduce the need for invasive measurements, or to accommodate measurement artifacts through signal processing. If practical, it will also ask how statistical methods can be used to reduce signal noise.

Other outcomes of high relevance:

The following learning outcome is highly relevant to the content and practice in BIOEN 316, but will not be used for program assessment.

(e) An ability to identify, formulate, and solve engineering problems. Examples in lecture and on problem sets will show how practicing bioengineers have identified needs in the biomedical community, and the strategies they have used to achieve solutions through engineering.

(j) A knowledge of contemporary issues. Example: The appropriateness of some diagnostic tests is the subject of some debate. In some cases the tests have a higher probability of producing a false positive result than a true positive result. Another example is computed axial tomography, which can be effective at detecting tumors but which also produces radiation that has been liked to carcinogenesis.

Relationship of Course to Departmental Objectives:

The goal of our Bachelors program in Bioengineering is to prepare our graduates for industry, graduate programs, and medicine. BIOEN 316 contributes to this goal by preparing students to do the following:

  1. Earn advanced degrees and/or obtain employment in bioengineering related fields, such as medicine, device development, or biotechnology.
  2. Advance their careers by obtaining appropriate educational and professional qualifications.
  3. Serve their profession and community.
  4. Contribute to responsible development of new technical knowledge.
  5. Take leadership roles in addressing domestic or global bioengineering related issues.

BIOEN 316 introduces junior‐level Bioengineering students to fundamentals of signal analysis and manipulation including universal quantitative analysis tools such as Fourier analysis, analysis of electrical and optical signals that are ubiquitous in biosensing, as well as their qualitative understanding of the performance of frequency‐domain filters and various biomedical sensors. This background is expected to increase their potential for employment.

BIOEN 316 introduces students to the terminology and procedures used in a variety of engineering disciplines and in the medical profession. In this way, it prepares our students to pursue opportunities for professional growth and eventually take leadership roles, across an expanding range of fields and thereby increases their potential impact in their profession and community.

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