CSCI 7000: Current Topics in Computer Science: Wearable/Mobile System for Health - Tam Vu

CSCI 7000: Current Topics in Computer Science: Wearable/Mobile System for Health

Fall 2019

General Information
  • Course number: CSCI 7000
  • Instructors: Tam Vu
  • Email: Tam [dot] vu [at] colorado [dot] edu
  • Class hours: W, F 12:00PM - 1:00PM
  • Class location: ECES 114
  • Office hour is by appointment
  • Office location: ECAE 151

Course overview

In recent years, the ability to continuously monitor activities, health, and lifestyles of individuals using sensor technologies has reached unprecedented levels. Wearable "on-body" sensors now enable routine and continuous monitoring of a host of physiological signals (e.g., heart rate, blood pressure, respiratory rate, blood glucose, etc.), physical activity (e.g. calorie expenditure), and sleep patterns. In addition, the typical smartphone comes routinely equipped with a plethora of sensors for monitoring both activity and location, enabling (in combination with other sensors) higher-order inferences about more complex human activities/behavioral states (e.g., stress, addiction, etc.). Such ubiquitous sensing in daily life, referred to as mobile health, promises to revolutionize our understanding of the varied social, environmental, and behavioral context (and potentially determinants) of a wide range of human activities and health conditions.

This course is an exploration of challenges in mobile health including: a) practical considerations including energy-efficiency, interruptions, wearability, privacy, etc. b) inference of key health assessments from sensor data including stress, mood, eating behavior, sleep patterns, calorie intake and expenditure, mental health, etc. c) personalized health assessment by combining continuous mobile sensor data using a variety of on-body sensors (chestband, wristband, smartphone) d) novel interventions that can take advantage of these models to elicit changes in health behavior. Students from diverse research backgrounds/interests are encouraged to attend for more productive discussion.

Course Credits: Three (3).

Reading List (subject to change)

    1- "PDVocal: Towards Privacy-preserving Parkinson's Disease Early Detection using Passive Body Sounds in Daily Life", Hanbin Zhang, Chen Song, Aosen Wang; Dongmei Li; Wenyao Xu. ACM MobiCom 2019

    2 - "Prediction of Mood Instability using Passive Sensing", Mehrab Bin Morshed, Koustuv Saha, Richard Li, Sidney D'Mello, Munmun De Choudhury, Gregory D Abowd, Thomas Ploetz, UbiComp 2019.

    3 - "Multi-Stage Receptivity Model for Mobile Just-In-Time Health Intervention", Woohyeok Choi, Sangkeun Park, Duyeon Kim, Youn-Kyung Lim, Uichin Lee, UbiComp 2019

    4 - "Identifying and Planning for Individualized Change: Patient-Provider Collaboration Using Lightweight Food Diaries in Healthy Eating and Irritable Bowel Syndrome", Chia-Fang Chung, Qiaosi Wang, Jessica Schroeder, Allison Cole, Jasmine Zia, James Fogarty, Sean A. Munson, UbiComp 2019

    5 - "Just-in-Time but Not Too Much: Determining Treatment Timing in Mobile Health", Peng Liao, Walter Dempsey, Hillol Sarker, Syed Monowar Hossain, Mustafa Al'Absi, Predrag Klasnja, Susan Murphy, Ubicomp 2019.

    6 - "Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants using Wearable Accelerometers", Yan Gao, Yang Long, Yu Guan, Anna Basu, Jessica Baggaley, Thomas Ploetz, UbiComp 2019.

    7 - "Tracking Fatigue and Health State in Multiple Sclerosis Patients Using Connected Wellness Devices", Catherine Tong, Matthew Craner, Angela Chieh, Otmane Bellahsen, Matthieu Vegreville, Eva Roitman, Nicholas D Lane, UbiComp 2019.

    7 - "Reconstructing Human Joint Motion with Computational Fabrics". Ruibo Liu, Qijia Shao, Siqi Wang, Christina Ru, Devin Balkcom, and Xia Zhou, UbiComp 2019

    8 - "On-body Sensing of Cocaine Craving, Euphoria and Drug-Seeking Behavior Using Cardiac and Respiratory Signals", Bhanu Teja Gullapalli, Annamalai Natarajan, Gustavo A. Angarita, Robert T. Malison, Deepak Ganesan, Tauhidur Rahman, UbiComp 2019.

    9 - "Fabric as a Sensor: Towards Unobtrusive Sensing of Human Behavior with Triboelectric Textiles Ali Kiaghadi, Morgan Baima, Jeremy Gummeson, Trisha Andrew, Deepak Ganesan, Sensys 2018.

    10 - "BreathListener: Fine-grained Breathing Monitoring in Driving Environments Utilizing Acoustic Signals", Xiangyu Xu, Jiadi Yu, Yingying Chen, Yanmin Zhu, Linghe Kong, Minglu Li, MobiSys 2019

    11 - "Animal-Borne Anti-Poaching System", György Kalmár, George Wittemyer, Péter Völgyesi, Henrik Barner Rasmussen, Miklós Maróti , Ákos Lédeczi, MobiSys 2019

    12 - "mCerebrum: A Mobile Sensing Software Platform for Development and Validation of Digital Biomarkers and Interventions", Syed Monowar Hossain, Timothy Hnat, Nazir Saleheen, Nusrat Jahan Nasrin, Joseph Noor, Bo-Jhang Ho, Tyson Condie, Mani Srivastava and Santosh Kumar, Sensys 2017

    13- "Monitoring a Person's Heart Rate and Respiratory Rate on a Shared Bed Using Geophones", Zhenhua Jia, Amelie Bonde, Sugang Li, Chenren Xu, Jingxian Wang, Yanyong Zhang, Richard E. Howard and Pei Zhang, SenSys 2017

    14 - "Ultra-Low Power Gaze Tracking for Virtual Reality", Tianxing Li, Qiang Liu and Xia Zhou, SenSys 2017

    15 - "Opioid Overdose Detection Using Smartphones", Rajalakshmi Nandakumar, Shyam Gollakota and Jacob Sunshine. Science Translational Medicine, 2019

    16 - "Contactless cardiac arrest detection using smart devices", Justin Chan, Thomas Rea, Shyam Gollakota and Jacob Sunshine. npj Digital Medicine, 2019

    17 - "Detecting middle ear fluid using smartphones", Justin Chan, Sharat Raju, Rajalakshmi Nandakumar, Randall Bly and Shyam Gollakota. Science Translational Medicine, 2019

    18 - "W!NCE: Unobtrusive Sensing of Upper Facial Action Units with EOG-based Eyewear", Soha Rostaminia, Alexander Lamson, Subhransu Maji, Tauhidur Rahman, Deepak Ganesan, Proceedings of ACM Interact. Mob. Wearable Ubiquitous Technol. Ubicomp 2019.

    19 - Contactless Infant Monitoring using White Noise, Anran Wang, Jacob Sunshine, Shyamnath Gollakota

    19 - Drunk User Interfaces: Determining Blood Alcohol Level through Everyday Smartphone Tasks, Alex Mariakakis, Sayna Parsi, Shwetak Patel, Jacob O. Wobbrock, CHI 2018

    20 - "iLid: Low-power Sensing of Fatigue and Drowsiness Measures on a Computational Eyeglass", Soha Rostaminia, Addison Mayberry, Deepak Ganesan, Benjamin Marlin, Jeremy Gummeson, Ubicomp 2017.

    TEMPORARY grouping:
    1/ Daily Activities Sensing: Paper 1, Paper 2, Paper 4, Paper 14
    2/ Vital Signs Sensing: Paper 9, Paper 11, Paper 16, Paper 19
    3/ Physiological Sensing: Paper 2, Paper 6, Paper 18, Paper 20
    4/ Medical Applications: Paper 5, Paper 6, Paper 15, Paper 16
    5/ Others: Paper 3, Paper 10, Paper 17

Course Grade
      Paper Reviews 30%
      Presentation 20%
      Projects 50%

    Letter Grades are as follows:

    • A –“Superior/Excellent”, 90 – 100%
    • B –“Good/Better than Average”, 80 – 89%
    • C –“Competent/Average”, 70 – 79%
    • D –“Minimum Passing”, 60 – 69%
    • F –“Failing”

Course procedures
  • Extension/Make-ups: In general, late work will not be accepted. Turn in all work by the established deadline. In case you have difficulties finishing an assignment, contact the instructor before the deadline. Late work can be accepted only under circumstances beyond student's control and after arrangement with the instructor, prior to the deadline. Note: work turned-in on time is eligible for partial credit. It will always be better to turn work in by the deadline, as trying to "perfect" it and turn it in late will give you no points at all. You have to follow the submission and media policies and guidelines written in the syllabus. Plagiarism is the passing of someone else's work as one's own, without giving the original author due credit. Scholastic dishonesty will be treated very strictly as per University of Colorado Boulder rules.

  • Lectures: Lecture materials will be made available on the web right after the class. Lecture will also consist of chalk drawings, overhead drawings, readings, and content not explicitly present in slides and notes.

  • E-mail Policy: I will be using the University e-mail system. I will be checking my email frequently and you can expect a response within 48 hours (holidays excluded). All email communication by students must use colorado.edu as the email domain, emails from gmail, hotmail, yahoo, etc are NOT considered valid methods of communication.

    • Student Expectations

  • Civility: My commitment is to create a climate for learning characterized by respect for each other and the contributions each person makes to class. I ask that you make a similar commitment.

  • Professionalism: Since mobile devices can be distracting during class, I ask that all devices be put into “silent” mode and not utilized during class; this includes checking Facebook, sending a Tweet, or checking e-mail. If I feel that your mobile device is becoming a distraction for either other students, you, or myself I will ask you to leave the classroom. Additionally, playing videos or other music without the use of headphones is prohibited. Headphones can only be used during open lab (not during announcements and lecture).

  • Religious Observations: I understand that an individual’s religion plays a large part in their lives and I do not want this course to interfere with that aspect of their lives. If you find that your religions holiday(s) falls on a class day and you cannot attend due to this, please notify me prior to that class date by e-mail and we can work together to find an acceptable solution.

  • E-mail Policy: I will be using the University e-mail system. I will be checking my email frequently and you can expect a response within 48 hours (holidays excluded). All email communication by students must use colorado.edu as the email domain, emails from gmail, hotmail, yahoo, etc are NOT considered valid methods of communication.

    • Collaboration and Cheating

    I encourage you to review material and discuss ideas together for the assignments and to work on problems you encounter. It is a characteristic of computation that discussions often help to clarify problems and resolve difficulties – feel free to take advantage of this to improve your understanding of the material, and to complete labs, but make sure that you then create your own work . It’s important that you go through the program design, coding, and debugging process yourself, or you will not be developing your own programming skills and understand. “Working together” does not mean that one student does the majority of the work and other students put their name on it! If you have questions about what this means, please see me. Every student must create their own work on their own! (this is easy to check for, so do your own work).

    Any instances of checking will result in either a zero for the lab, a grade of zero in the course, or sanctions determined by the university (including suspension and expulsion).

    University Policies

    Academic Honesty and Student Code of Conduct: Students are expected to know, understand, and comply with the ethical standards of the university, including rules against plagiarism, cheating, fabrication and falsification, multiple submissions, misuse of academic materials, and complicity in academic dishonesty.

    Copyright © Tam Vu 2019