I am a PhD student in Mobile and Networked System Lab supervised by Prof. Tam Vu at the University of Colorado Boulder.
► I obtained my B.S from the University of Science in Ho Chi Minh City.
► I received the M.S degree in Computer Science and Entrepreneurship at the University of Nottingham.
► The following prizes have been awarded to my works: Best Paper Nominee (ACM SenSys 2017), Best Paper Award (ACM MobiCom-S3 2017-2018), 2nd prize (ACM MobiCom'17 App Contest).
Stunning photos I took during my travells.
ACM Transactions on Sensor Networks (TOSN)
Impact factor: 2.313.
ACM MobiCom 2019
(55 out of 290 submissions, acceptance ratio: 18.9%).Best Paper Award 2019
PDF Intro Slides
eBP: A Wearable System For Frequent and Comfortable Blood Pressure Monitoring From User’s EarBest Paper Award 2019
PDF Demo Slides
Frequent blood pressure (BP) assessment is key to the diagnosis and treatment of many severe diseases, such as heart failure, kidney failure, hypertension, and hemodialysis. Current “gold-standard” BP measurement techniques require the complete blockage of blood flow, which causes discomfort and disruption to normal activity when the assessment is done repetitively and frequently. Unfortunately, patients with hypertension or hemodialysis often have to get their BP measured every 15 minutes for a duration of 4-5 hours or more. The discomfort of wearing a cumbersome and limited mobility device a#ects their normal activities. In this work, we propose a device called eBP to measure BP from inside the user’s ear aiming to minimize the measurement’s impact on users’ normal activities while maximizing its comfort level. eBP has 3 key components: (1) a light-based pulse sensor attached on an infatable pipe that goes inside the ear, (2) a digital air pump with a !ne controller, and (3) a BP estimation algorithm. In contrast to existing devices, eBP introduces a novel technique that eliminates the need to block the blood fow inside the ear, which alleviates the user’s discomfort. We prototyped eBP custom hardware and software and evaluated the system through a comparative study on 35 subjects. The study shows that eBP obtains the average error of 1.8 mmHg and -3.1 mmHg and a standard deviation error
Pediatric Pulmonology Journal
Impact factor: 3.159.
ACM SenSys 2018
(23 out of 147 submissions, acceptance ratio: 15.6%).Best Paper Runner-Up 2018
CapBand: Battery-free Successive Capacitance Sensing Wristband for Hand Gesture RecognitionBest Paper Runner-Up 2018
We present CapBand, a battery-free hand gesture recognition wearable in the form of a wristband. The key challenges in creating such a system are (1) to sense useful hand gestures at ultra-low power so that the device can be powered by the limited energy harvestable from the surrounding environment and (2) to make the system work reliably without requiring training every time a user puts on the wristband. We present successive capacitance sensing, an ultra-low power sensing technique, to capture small skin deformations due to muscle and tendon movements on the user’s wrist, which corresponds to speci!c groups of wrist muscles representing the gestures being performed. We build a wrist muscles-to-gesture model, based on which we develop a hand gesture classi!cation method using both motion and static features. To eliminate the need for per-usage training, we propose a kernel-based on-wrist localization technique to detect the CapBand’s position on the user’s wrist. We prototype CapBand with a custom-designed capacitance sensor array on two flexible circuits driven by a custom-built electronic board, a heterogeneous material-made, deformable silicone band, and a custom-built energy harvesting and management module. Evaluations on 20 subjects show 95.0% accuracy of gesture recognition when recognizing 15 di#erent hand gestures and 95.3% accuracy of on-wrist localization.
ACM MobiSys 2018
(37 out of 138 submissions, acceptance ratio: 26.8%).PDF Demo Slides
TYTH-Typing On Your Teeth: Tongue-Teeth Localization for Human-Computer InterfacePDF Demo Slides
This paper explores a new wearable system, called TYTH, that enables a novel form of human computer interaction based on the relative location and interaction between the user’s tongue and teeth. TYTH allows its user to interact with a computing system by tapping on their teeth. This form of interaction is analogous to using a finger to type on a keypad except that the tongue substitutes for the finger and the teeth for the keyboard. We study the neurological and anatomical structures of the tongue to design TYTH so that the obtrusiveness and social awkwardness caused by the wearable is minimized while maximizing its accuracy and sensing sensitivity. From behind the user’s ears, TYTH senses the brain signals and muscle signals that control tongue movement sent from the brain and captures the miniature skin surface deformation caused by tongue movement. We model the relationship between tongue movement and the signals recorded, from which a tongue localization technique and tongue-teeth tapping detection technique are derived. Through a prototyping implementation and an evaluation with 15 subjects, we show that TYTH can be used as a form of hands-free human computer interaction with 88.61% detection rate and promising adoption rate by users.
ACM SenSys 2017
(26 out of 151 submissions, acceptance ratio: 17.2%).Best Paper Award Nominee 2017 2nd Prize ACM MobiCom 2017 App Contest
PDF Demo Slides
PhO2: Smartphone based Blood Oxygen Level Measurement Systems using Near-IR and RED Wave-guided LightBest Paper Award Nominee 2017 2nd Prize ACM MobiCom 2017 App Contest
PDF Demo Slides
Accurately measuring and monitoring patient's blood oxygen level plays a critical role in today's clinical diagnosis and healthcare practices. Existing techniques however either require a dedicated hardware or produce inaccurate measurements. To fill in this gap, we propose a phone-based oxygen level estimation system, called PhO2, using camera and flashlight functions that are readily available on today's off-the-shelf smart phones. Since phone's camera and flashlight are not made for this purpose, utilizing them for oxygen level estimation poses many challenges. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A light-based pressure detection algorithm and feedback mechanism are also proposed to mitigate the negative impacts of user's behavior during the measurement. We also derive a non-linear referencing model that allows PhO2 to estimate the oxygen level from color intensity ratios produced by smartphone's camera.
An evaluation using a custom-built optical element on COTS smartphone with 6 subjects shows that PhO2 can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. A user study to gauge the reception of PhO2 shows that users are comfortable self-operating the device, and willing to carry the device when going out.
ACM MobiCom 2017 - S3 Workshop
Best Paper Award
American Thoracic Society 2017 International Conference
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
2017 nowBoulder, CO
COMPUTER SCIENCE - PHD
UNIVERSITY OF COLORADO, BOULDERAdvisor: Prof. Tam Vu
2016 2017Denver, CO
UNIVERSITY OF COLORADO, DENVERAdvisor: Prof. Tam Vu.
COMPUTER SCIENCE AND ENTREPRENEURSHIP
THE UNIVERSITY OF NOTTINGHAM - MasterAdvisor: Prof. Tomas Maul.
MATHEMATICS AND COMPUTER SCIENCE
UNIVERSITY OF SCIENCE - BachelorAdvisor: Prof. The-Bao Pham
- ACADEMIC AND PROFESSIONAL POSITIONS
2013 2016Gwangju, Korea
GRADUATE STUDENT RESEARCHER
CHONNAM NATIONAL UNIVERSITYAdvisor: Prof. Jin-young Kim
UNIVERSITY OF SCIENCE HCMCAdvisor: Prof. The-Bao Pham.
UNIVERSITY OF SCIENCE HCMCAdvisor: Prof. The-Bao Pham.
- HONORS AND AWARDS
► Best Paper Award Nominee, ACM SenSys 2017.
► 2nd prize at to ACM MobiCom'17 App Contest.
► Best Paper Award, ACM MobiCom-S3 (Oct. 2017).
► Awarded Excellent Oral Presentation at ISIPS 2015, Waseda University, Japan.
► Awarded Excellent Poster Presentation at ISIPS 2014, Waseda University, Japan.
► Funding recipient of Nationwide Brain Korea 21 Program for Leading Universities & Students (BK21 PLUS) to publish at least one SCI/SCIE scientific journal per year from 2013 to 2016.
► Recipient of the Information Technology Research Center (ITRC) Scholarship (from 2013~2016).
► Recipient of University of Nottingham Malaysia Campus 2010 Developing Solutions Masters Scholarship.
► Student’s science research contest – Mathematics and Computer Sciences: Winner (Final year 2008-2009).
► The adventure of finding solution – Mathematics and Computer Sciences: 2nd runner up (1st year 2005-2006).
Blood Oxygen Level Measurement System Using Smartphone Camera
In this project, we propose a phone-based oxygen level estimation system using camera that are readily available on today’s off-the-shelf smart phones. Since phone’s camera is not made for this purpose, utilizing it for oxygen level estimation poses many challenges. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A light-based pressure detection algorithm and feedback mechanism are also proposed to mitigate the negative impacts of user’s behavior during the measurement. We also derive a non-linear referencing model that allows our system to estimate the oxygen level from color intensity ratios produced by smartphone’s camera.
► Nam Bui
► Anh Nguyen
► Phuc Nguyen
► Hoang Truong
► Robin Deterding
► Tam Vu (Advisor)