ECE 382V Human Signals: Sensing and Analytics (Spring 2025)

Unique: 18175
Time: TTH 2:00 to 3:30pm
Location: ECJ 1.314

Instructor: Edison Thomaz (ethomaz at utexas dot edu, or contact through Canvas)
Office Hours: Thursdays 3:30-4:30pm or by appointment
Office Hours Location: EER 7.818

TA: Gautham Gudur (gauthamkrishna at utexas dot edu, or contact through Canvas)
Office Hours: 2:30-3:30pm
Office Hours Location: EER 7.652

Online Forum: We will be using Ed Discussion, which you can access through Canvas.

Paper Critique Form: You should post your critique using Canvas. An assignment has been created for each lecture.

Description

This course is aimed at gradute students and has 2 objectives. The first one is to teach concepts and practical skills for building systems that can sense and infer human signals (behavioral, physiological, emotional) and their respective context while leveraging mobile, ubiquitous and wearable computing technologies. The second aim is to examine and discuss advanced and emerging topics in the field in a seminar-style setting. Students will work on assignments throughout the semester, complete a project in a topic of their choosing, read and critique papers, present papers in class, and lead discussions. Key topics covered include machine learning fundamentals, activity recognition, sensing approaches (on-body, environmental), sensing modalities (e.g., inertial, acoustic, vision), sensor signal processing, and digital phenotyping.

Requirements

Academic: Graduate standing (or undergraduate with instructor approval). At a basic level, students will be expected to be comfortable using a high-level programming language. Experience with machine learning and related toolkits such as scikit-learn as well as mobile programming (iOS or Android) is useful but not required; we will review key concepts in the first part of the course. All the programming work in this class will be in Python and the Anaconda scientific package. If you are unsure if your background is a good match for this course, please come talk to the instructor.

Writing and Speaking: This course involves significant speaking and writing skills. Assignments must be completed in English. While primary assessment will focus on course material, correct spelling and grammar (along with coherence and logic) are expected and will be assessed in grading. Also, everyone is expected to participate in class and should be prepared for it. Class discussion each week is intended to reinforce understanding of the material. UT offers individual writing consultations to graduate students through the University Writing Center. Take advantage of these services, particularly before handing in project assignments (this of course requires starting early to get feedback from consultations and revise drafts accordingly).

Equipment: It is assumed that all students will have access to a computing system (i.e. laptop) to work on assignments. If you need assistance with computing resources, please contact the instructor.

Reading Materials

This class focuses on cutting-edge research in the field. Therefore, most of what we will read and discuss are recently-published papers. These will be provided to you by the instructor.

Schedule

Week Topic and Readings Assignment Project
Jan 14th Introduction
Jan 16th Machine Learning: Fundamentals A0 Out
Jan 21st Machine Learning: Methods and Evaluation
Jan 23rd Activity Recognition
Jan 28th Inertial Sensing I A1 Out
Jan 30th Inertial Sensing II
Feb 4th Inertial Sensing III (Team)
Feb 6th Acoustic Sensing I A1 Due
Feb 11th Acoustic Sensing II A2 Out
Feb 13th Vision Sensing I Proposal
Feb 18th Vision Sensing II
Feb 20th Environmental Sensing I A2 Due
Feb 25th Environmental Sensing II A3 Out
Feb 27th Multimodal Sensing
Mar 4th Interactive Activity Recognition
Mar 6th Adaptive and Lifelong Learning A3 Due
Mar 11th Privacy and Ethics I
Mar 13th Privacy and Ethics II
Mar 18th Spring Break (No class)
Mar 20th Spring Break (No class)
Mar 25th Health I (Clinical)
Mar 27th Health II (Behavior) Update
Apr 1st Health III (Dietary)
Apr 3rd Digital Phenotyping and Biomarkers I
Apr 8th Digital Phenotyping and Biomarkers II
Apr 10th Digital Phenotyping and Biomarkers III
Apr 15th Project Presentations
Apr 17th Project Presentations
Apr 22nd Project Presentations
Apr 24th Project Presentations Report
Apr 25th Critiques

Class Activities and Deliverables

At a high-level, there are 5 key activities, tasks and deliverables that students will be responsible for in this course:

Specific details about these activities and deliverables are provided in the sections below.

Paper Reading: Critique + Discussion Points

All students in the class will be expected to read the required paper assigned for each lecture. The papers will be provided to you by the instructor. Additionally, each student will be expected to submit a one or two paragraph critique of the paper and two discussion points through Canvas. You will be graded on your communication and the quality and depth of your critique and discussion points. A few discussion points will be selected for class discussion. These points could be elements of the paper that you did not understand or specific questions that emerged while you were reading the paper (e.g., about the methodology, instrumentation, user study, data analysis, motivation). To write your critique and come up with the two discussion points, here are some examples of questions you could ask yourself while reading and examining papers:

Paper Presentation

Once during the semester, each student will be assigned a paper to present to the class. The presentation should be equivalent to a 10-minute conference-style talk, with 5 additional minutes for discussion, for a total of 15 minutes per paper. As the paper “expert”, the student presenter will be required to read the paper in detail and prepare (1) a set of slides to show in class, and (2) be ready to answer clarification questions. We will do our best to match students with their topic of choice; this assignment will be established in the first weeks of class. Students should consider these presentations to be like exams. If a student is not available to present his or her assigned paper (without advance notification), the student will get zero credit for this portion of the course grade. Students should communicate with the instructor at least one week before the scheduled presentation if they will not be available to present on the assigned day. Students will be also expected to upload the slides they presented to Canvas.

Assignments

Students will work on three assignments during the semester. The assignments will be due approximately 10 days after they have been made available. The assignments will be on the topics of inertial sensing, acoustic sensing and vision sensing.

Group Project

Students will be required to complete a class group project. Each group should have 3-4 student members. It is recommended that the team is in place at least one week before the proposal is due. Projects will let students choose a particular topic of their interest and study it in more depth. It is not expected to represent completely original research but students are encouraged to think creatively. It is ok to build on previous ideas and studies. Project ideas will be provided to you by the instructor. Three deliverables will be expected as part of the project: (1) a proposal, (2) a final report, (3) a 15 minute conference-style presentation with slides, and (4) a critique of other projects following the project presentations at the end of the semester.

Proposal

The first project deliverable will be the project proposal, which should be no longer than 2 pages and include all the sections below. The proposal will be graded on the basis of completeness and clarity for each one of the sections, as well as novelty. Students should discuss their project and proposal with the instructor and/or the TA before submission.

Progress Update Report

The project update should be no longer than 2 pages and include all the sections below. The goal of this document is to communicate how your project is progressing, whether you are running into unanticipated challenges, and what you are planning to do to mitigate these challenges.

Final Report

The report should not be longer than 10 pages (one-column) plus references, following the ACM single-column format. Graphs and images are ok. You may submit appendices which include design documents or other diagrams such as circuit layouts. These will not count towards the page limit. Refer to the papers we have read in class for pointers on how to present your work in writing. Links to the Latex and Word templates for this format can be found here. At a minimum, your paper must include the sections below:

Final Presentation

At the end of the semester our class will be dedicated to project presentations. Students will be expected to deliver a 15-minute conference-style presentation with slides and then answer questions afterwards for 5 minutes. The presentations will be expected to include a technical description of the project and motivation, methods useds, related work, and key take ways, e.g., what you learned. Clarity of communication and quality of the presentation slides will also be part of the grading criteria.

Final Project Presentations Critique

All students will be expected to attend all project presentations, and presence and participation during this final stage of the course will constitute a significant portion of the course participation grade. Additionally, all students will be expected to submit a brief written critique of all projects. This project critique should follow the same guidelines as the paper critiques.

Course Participation

Students are expected to attend every lecture and participate in discussions. Participation is not optional; the instructor will actively engage with students throughout the semester. The course participation grade will be assigned to every student based on this engagement.

Grading

Here is a breakdown of how the final grade for each student will be computed:

Grade Distribution:

Grade Disputes and Corrections: If you are dissatisfied with a grade you receive, you must submit your complaint briefly in writing or by email, along with supporting evidence or arguments, to your TA within one week of the date that I (or the TA) first attempted to return the exam or assignment results to you. For programming assignments the dispute period starts with the posting of your score on the class Canvas gradebook page. Complaints about grades received after the one-week deadline will be considered only if there are extraordinary circumstances for missing the deadline (e.g. student hospitalization). No new disputes will be accepted after 11:59AM three days before the course grade sheets must be turned in.

The grade you are given, either on an individual exam or assignment or as your final grade, is not the starting point of a negotiation. It is your grade unless a concrete grading error has been made. Do not come to see the instructor or the TA to ask for a better grade because you want one or you "feel you deserve it". Come only if you can document a specific error in grading or in recording your scores. Errors can certainly be made in grading, especially when large classes of many students are involved. But keep in mind that the errors can be made either in your favor or not. So it's possible that if you ask to have a piece of work re-graded your grade will go down rather than up.

Remember that the most important characteristic of any grading scheme is that it be fair to everyone in the class. Keep this in mind if you're thinking of asking, for example, for more partial credit points on a problem. The important thing is not the exact number of points that were taken off for each kind of mistake. The important thing is that the number was the same for everyone. So it may not be changed once the grading is done and the exams or assignments have been returned. If you have questions or concerns about any of your grades, contact your TA first, and if not satisfied with that interaction then contact the instructor during office hours or via email.

Late Deliverables

Late deliverables will be accepted for 3 days after their due date but 30 points (out of 100 points) will be automatically deducted. This will apply only to the assignments, the project proposal, the project update, and the project report. After 3 days, late deliverables will receive a zero. In the interest of fairness, there will not be any exceptions to this policy.

Absences and/or Missed Deadlines Due to Illness

If you miss deadlines or presentations due to illness, please bring the instructor a doctor's note that indicates not only that you had a medical consultation but also reports the actual illness that was diagnosed. If such note is provided, the instructor will be happy to make accomodations and extend deadlines. Otherwise, all other policies apply (e.g., late deliverables).

Absences and/or Missed Deadlines Due to Other Reasons

It is understandable that students might need to travel due to conferences, interviews, legal matters, or other reasons usually tied to their academic work or professional development. Extensions for these reasons are exceptional but might be made at the discretion of the instructor upon documentation. Even in these circumstances, students should plan well in advance to avoid missing deadlines. Extensions for personal reasons will not be granted.

Exams

There will not be a midterm or final exam for this course.

Sharing of Course Materials is Prohibited

No materials used in this class, including, but not limited to, lecture hand-outs, videos, assessments (quizzes, exams, papers, projects, homework assignments), in-class materials, review sheets, and additional problem sets, may be shared online or with anyone outside of the class unless you have my explicit, written permission. Unauthorized sharing of materials promotes cheating. It is a violation of the University’s Student Honor Code and an act of academic dishonesty. I am well aware of the sites used for sharing materials, and any materials found online that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.

FERPA and Class Recordings

Class recordings, if available, are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction by a student could lead to Student Misconduct proceedings.

Standard UT Austin Course Information and Policies

Academic Honor Code: You are encouraged to discuss assignments with classmates, but anything submitted must reflect your own, original work. If in doubt, ask the instructor. Plagiarism and similar conduct represents a serious violation of UT's Honor Code and standards of conduct.

Students who violate University rules on academic dishonesty are subject to severe disciplinary penalties, such as automatically failing the course and potentially being dismissed from the University. Please do not take the risk. We are required to automatically report any suspected case to central administration for investigation and disciplinary hearings. Honor code violations ultimately harm yourself as well as other students, and the integrity of the University.

Academic honesty is strictly enforced.

Notice about students with disabilities: The University of Texas at Austin provides appropriate accommodations for qualified students with disabilities. Please check UT Disability and Access. If they certify your needs, we will work with you to make appropriate arrangements. Any students requiring assistance in evacuation must inform the instructor in writing of their needs during the first week of classes.

Coping with stress and personal hardships: The Counseling and Mental Health Center offers a variety of services for students, including both individual counselling and groups and classes, to provide support and assistance for anyone coping with difficult issues in their personal lives. As mentioned above, life brings unexpected surprises to all of us. If you are facing any personal difficulties in coping with challenges facing you, definitely consider the various services offered and do not be shy to take advantage of them if they might help. These services exist to be used.

Notice about missed work due to religious holy days: A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.

Electronic Mail Notification Policy: In this course e-mail, Canvas will be used as a means of communication with students. You will be responsible for checking your e-mail regularly for class work and announcements. If you are an employee of the University, your e-mail address in Canvas is your employee address.

The University has an official e-mail student notification policy. It is the student's responsibility to keep the University informed as to changes in his or her e-mail address. Students are expected to check e-mail on a frequent and regular basis in order to stay current with University-related communications, recognizing that certain communications may be time-critical.

Edison Thomaz © 2025