Research

My research focuses on human-centric ubiquitous computing, with an emphasis on using Internet of Things (IoT) sensors to empower interaction and healthcare applications. In particular, I am interested in using IoT sensors to interpret and understand physical and physiological human behaviors.

Currently, I am working on the following two directions:

1. Immersive HCI techniqes and

2. Smart pulmonary disease management.

RimSense: Enabling Touch-based Interaction on Eyeglass Rim Using Piezoelectric Sensors

W Xie, H Chen, J Wei, J Zhang, Q Zhang (IMWUT/UbiComp 2024)
RimSense supports touch gestures on the eyeglass rim using piezoelectric sensors. This design enables direct manipulation-based interaction.   Paper   Demo

BLEAR: Practical Wireless Earphone Tracking under BLE protocol

L Ge, W Xie, J Zhang, Q Zhang (PerCom 2024)
BLEAR is an earphone-based position tracking system which can truly be adopted under the BLE protol with restricted sampling rate.

Acoustic-based Upper Facial Action Recognition for Smart Eyewear

W Xie, Q Zhang, J Zhang (IMWUT/UbiComp 2021)
Fasense is a smart eyewear design that incorporates pairs of acoustic sensors to sense upper facial actions for immersive interaction.
Paper   Talk   Demo

DeepBreath: Breathing Exercise Assessment with a Depth Camera

W Xie, C Xu, Y Gong, Y Wang, Y Liu, J Zhang, Q Zhang, Z Zheng, S Yang (IMWUT/UbiComp 2024)
DeepBreath is a depth camera-based breathing training system that can measure breathing rate, breathing volume and breathing mode (chest/belly).   Paper   Demo

EarSpiro: Earphone-based Spirometry for Lung Function Assessment

W Xie, Q Hu, J Zhang, Q Zhang (IMWUT/UbiComp 2022)
EarSpiro is a cost-efficient pulmonary function test (PFT) method with a pair of mic-caring earphones. EarSpiro can estimate F-V curves and PFT indicators.   Paper   Demo

Noncontact Respiration Detection Leveraging Music and Broadcast Signals

W Xie, R Tian, J Zhang, Q Zhang (IoTJ 2020)
This work presents a breathing rate estimation methods with a pair of microphone and speaker, with any music pieces.
Paper

PDAssess: A Privacy-preserving Free-speech based Parkinson’s Disease Daily Assessment System”

B Yang, Q Hu, W Xie, X Wang, W Luo, Q Zhang (SenSys 2023)
PDAssess is a free speech-based Parkinson’s Disease (PD) severity assessment system, which can be installed on commodity smart speakers.