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Wearable and Wireless Cyber-Physical Systems for Non-invasive Sleep Quality Monitoring

Date and Time
Thursday, April 6, 2017 - 12:30pm to 1:30pm
Computer Science Small Auditorium (Room 105)
CS Department Colloquium Series
Prof. Jennifer Rexford

Sleep occupies nearly a third of human’s life and acts as a critical daily function, helping our body to balance and regulate vital systems. However, in the United States, more than 35% of the population is sleep deprived. Therefore, quantifying sleep quality is important and has significant clinical value in detecting and diagnosing various sleep-related disorders. Unfortunately, the current “gold standard” for studying patients’ sleep is obtrusive, expensive, and often inaccurate.

In this talk, I will introduce our wearable and radio-based sensing systems that promise unobtrusive, low-cost, and accurate sleep study for in-hospital and in-home settings. I will start with WiSpiro, a sensing system that is able to unobtrusively monitor breathing volume and detect sleep disorder breathing in patients using radio signals from afar. I will then discuss LIBS, an in-ear wearable sensing system that can simultaneously monitor human’s brain activities, eye movement, and facial movement, which are critical for fine-grained sleep stage monitoring.  I will also identify other potential uses of these systems in a broader context of health care, such as monitoring eating habits and disorders, detecting autism at early stages, improving neurological surgery practice, and detecting seizure. I will conclude the talk by discussing my on-going research as well as my future directions to improve current health care practices through the development of other innovative cyber-physical healthcare systems.

Tam Vu is directing Mobile and Networked Systems (MNS) Lab at University of Colorado Boulder, where he and his team work on building systems to improve pediatric health care practices. At MNS, he designs and implements novel and practical cyber-physical systems to make physiological sensing (e.g. breathing volume measurement, brainwave signal monitoring, muscle movement recording, and sleep quality monitoring) less obtrusive at lower cost.

Tam Vu’s research contribution has been recognized with four best paper awards from ACM SenSys 2016, MobiCom S3 2016, MobiCom 2012, and MobiCom 2011; a Google Faculty Research Award in 2014; and wide press coverage including Denver Post, CNN TV, NY Times, The Wall Street Journal, National Public Radio (NPR), MIT Technology Review, Yahoo News. He is actively pushing his research outcome to practice through technology transfer activities with 9 patents filed in the last 3 years and forming 2 startups to commercialize them. He received his Ph.D. in Computer Science from WINLAB, Rutgers University in 2013 and a BS in Computer Science from Hanoi University of Technology in 2006.

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