Master Course Description for EE-484 (ABET sheet)

Title: Sensors and Sensor Systems

Credits: 4

UW Course Catalog Description

Coordinator: Denise Wilson, Professor, Electrical and Computer Engineering

Goals: This design course provides seniors whose area of concentration is sensors and devices with a capstone design experience in the open-ended design of sensor systems. It also provides other interested students with an overview of optical and physical sensors in the context of engineering design.

Learning Objectives: At the end of this course, students will be able to:

  1. Formulate and solve open-ended design problems in systems that require sensors to fulfill their function.
  2. Write formal project reports.
  3. Make formal project presentations.
  4. Work in teams with heterogeneous knowledge and skills.
  5. Apply governing mechanisms of particular sensor technologies, basic transduction mechanisms, noise properties, sources of environmental interference, and computer simulation to the design of complete sensor systems whose overall performance is defined and demonstrated using standardized system metrics.
  6. Demonstrate an awareness of benefits and drawbacks of predominant sensor technologies.

Textbook: Class notes, textbook excerpts, and journal articles

Reference Texts:

  1. Mike Markel, Writing in the Technical Fields, IEEE Publications
  2. Kellie Cook, "Layered Literacies: A Theoretical Frame for Technical Communication Pedagogy," Tech Communication Quarterly , Winter 2002, pp. 5-29.
  3. Cliff Atkinson, Beyond Bullet Points, Microsoft Press: 2005.


  • Devices and Circuits I (EE 331) or Instructor Permission
  • Prerequisites by Topic:

    1. Fundamental circuit analysis
    2. Discrete electronic circuit design
    3. Computer literacy with Matlab or Python, word processing, presentation and spreadsheet software
    4. Novice capability in Labview and Data Acquisition
    5. Fluency in basic electronic test equipment usage


    1. Introduction - 1 week
    2. Sensor Performance Metrics - 0.5 weeks
    3. Review of mechanical, biochemical, radiant, and thermal sensors - 4 weeks
    4. Engineering Design, Design of Experiments, and Statistical Analysis of Experimental Data: 2.5 weeks
    5. Project Reports, Presentations, and Design Project Feedback - 2 weeks

    Course Structure:

  • The class typically meets for two lectures a week, each consisting of one 100-minute session. Approximately half of these sessions are organized into short lectures on technical topics (sensors) or engineering design topics. The other half of sessions are committed to design project group activity, including presentations, feedback, and working design sessions. The design project begins at the start of the quarter with a project proposal followed by regularly spaced milestones throughout the quarter (Proposal; System Design; System Analysis and Simulation; Proof of Concept Results; System Characterization; Performance Figures of Merit; and Final Report). A written and oral project report from each team is due at the end of the course. There are no exams; however, many collaborative learning sessions and in-class design project group presentations will be graded.
  • Computer and Laboratory Resources:

  • Design projects require a combination of standard software packages (Matlab, Labview, Microsoft Excel/Word/Powerpoint) and test equipment resources (National Instruments Data Acquisition cards and standard EEB 137 multimeters, power supply, and oscilloscopes). LabVIEW is also available in the room 137 EEB laboratory, integrated with hardware for data acquisition. Matlab and other software are available in multiple computing labs in ECE and on campus.
  • Grading:

  • In-class exercises and short concept quizzes 30% of the grade; and the design project 70% of the grade.
  • ABET Student Outcome Coverage: This course addresses the following outcomes:

    H = high relevance, M = medium relevance, L = low relevance to course.

    (1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics (M) The design of sensor systems requires basic (science) understanding of the governing mechanisms of both sensor and transduction techniques. The interaction between sensor and transduction must also be understood mathematically (including noise analysis). The sensor system design problem presents itself as a series of interconnected engineering problems. In the open-ended design environment, the engineering problems are not explicitly stated, but must be identified and properly formulated by the design team before they can be solved. Students are expected to use mainstream math processing, data acquisition, and data presentation software to design, analyze, characterize, and summarize sensor system performance. Students must also use general purpose test equipment and electronic interface circuits to extract system performance from their designs. Evidence of the use of these tools in the context of solving a complex design problem appears in the design project milestones as well as the final report and presentation.

    (2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors (H) Sensor systems, in many cases, inherently aim to improve the environmental, health, safety, manufacturability, or social impact of a larger system. Students consider and implement the sensor system design in the context of defining (through a literature review and design proposal) a specific need for that system in society and having a targeted impact on that need. In addition to designing a system whose cost is consistent with typical product costs and profit margins for the industry to which the sensor system is a best fit, students also consider safety through the application of relevant standards as well as environmental and social impacts through considering three main pillars of sustainability.

    (3) An ability to communicate effectively with a range of audiences (H) Teams must prepare an extensive written project report, and make an oral presentation at the end of the class. Team contributions to the final report are submitted individually and as a final team product. Teams must demonstrate the "Beyond Bullets"/storytelling approach in their final oral presentation. Effectiveness of the storytelling approach is evaluated via a peer marketability survey (or similar peer review) of each sensor system. Final reports are graded based on layered technical writing literacies for effective and convincing technical writing.

    (4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts (M) Student design teams are required to consider in depth at least one of the three pillars of sustainability (economic, environmental, or social) in their final project reports and in a design project milestone. Course instruction includes multiple class sessions on ethical responsibility followed by in-class scenarios/problems where students consider unanticipated ethical ramifications of engineered and sensor systems.

    (5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives (H) Students work in teams of 3-4 individuals to design the sensor system in a community of learners format. Students offer heterogeneous expertise to the system design that evolves as a function of natural interest in particular aspects of the design over others. Students are allowed as much flexibility in assigning team function as possible within the constraints of completing a successful demonstration of their designs. Some students may focus on testing, others on statistical characterization of system performance, others on circuit design, others on sensor/transduction behavior derivation, and so on.

    (6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions (M) The design project requires that students benchmark performance metrics of their sensor systems against commercial systems to establish their usefulness in the designated market. Experiments must be designed to show, statistically, that sensor design remains within acceptable limits of the benchmark. Evidence of the proper design of experiments and extraction of performance metrics is shown in weekly design project team meetings and in the final project report.

    (7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies (L) Although EE484 is a culminating design course, students must be resourceful in gaining new knowledge about specific sensors and products that they choose for their final designs. Some of this knowledge is provided in class as the course evolves but most is gathered and processed by students on a need to know basis to support methodical and successful engineering design.

    Prepared By: Denise Wilson

    Last Revised: 01/16/19