EXERCISE -
Explore Emerging Computing in Science and Engineering
- National Science Foundation (NSF) Research Experiences for
Undergraduates (REU) Site
- I am a Faculty Associate, 2022-2025
Prototyping decision support and
monitoring tools for equitable management of salt contamination of
water supplies in tidal rivers (subaward)
- National Science Foundation (NSF) Convergence Accelerator Track K
- I am an investigator, Jan. 2024 - Dec. 2024
Gait Disturbance Measurement for
Preventing Older Adult Falls
- Salisbury University Faculty Mini-Grant
- I am the PI, 2020 - 2021
Note: Please contact me for potential funding opportunities.
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Vincent Pham
- Undergraduate student, Salisbury University
- Project: Spatio-Temporal Salinity Data Modeling and Visualization
for Salt Contamination Monitoring in the Chesapeake Bay Area
- Jun. 2024 - Aug. 2024
- Henson Summer Research Program
Mariamawit Yohannes
- Undergraduate student, Salisbury University
- Project: High-Accuracy Walking Surface Classification through Heel
Strike Detection
- Jun. 2024 - Aug. 2024
- SU Student Research Summer Program 2024
Olivia Brague
- Undergraduate student, Salisbury University
- Project: Promote honors student's critical thinking and research
abilities via conducting AI research project
- Title: Inferring handwriting inputs on smartphone with
side-channel information
- Sep. 2023 - Dec. 2023
- Honors Session Project
Stephora Alberi
- Undergraduate student, Salisbury University
- Project: High-performance deep learning model for emotion
detection
- Aug. 2023 - Dec. 2023
- COSC 390 Undergraduate Research Project
Joshua Comfort
- Undergraduate student, Salisbury University
- Project: PCA-Based Efficient CNN Model Construction for ASL
Recognition
- Presented as a Lightning Talk at the 2023 IEEE MIT
Undergraduate Research Technology Conference (CS
News & PowerPoint slides)
- Jan. 2023 - May 2023
- Supported by NSF RUI project
Ejiro Adams Ubini
- Undergraduate student, The Community college of Baltimore County
- Project:
Real-time Model Adaptation for WiFi Gesture Recognition
- Jun. 2022 - Aug. 2022
- Supported by
NSF
REU Site project
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Shimmer3 EMG Development Kit (Base6 +
2 Shimmer3)
This Kit contains two Shimmer3 devices. Each device has 9DoF motion
sensors (an accelerometer, a gyroscope, and a compass) and two
channels of EMGs.
Smartphone
SAMSUNG Galaxy A14 smartphone is available. It contains accelerometer,
gyroscope, compass, camera, microphone, etc.
(picture from internet)
Smart wristband
Garmin vívosmart® 5 is available. It contains an optical heart rate
monitor, an accelerometer, an ambient light sensor, and a blood
oxygen saturation (SpO2) monitor.
(picture from internet)
Note: please feel free to contact me if you need any of the above devices for your research and experiments.
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Our goal is to develop lightweight, high-performance, and robust machine learning algorithms and applications to recognize diverse activities through mobile and wearable devices and provide smart health-related services to the public.
The following are some interesting research topics in the fields of wearable intelligence and smart health. In each topic, there are some existing or ongoing projects. We will further investigate these projects to either improve the existing solutions or address the unresolved problems.
This topic aims to use wearable motion sensors to continuously monitor user's dietary activities, including eating detection, food type recognition, and chewing side detection.
Project 1-1: Eating activity
detection & chews counting
- This project aims to detect eating activity and count chews
through attaching a triaxial accelerometer on the temporalis.
- Research skills to learn: classification algorithms, digital
signal processing, programming language (Matlab or Python).
- Dataset is available.
- Reference:
S Wang et al., Eating detection and chews counting through sensing
mastication muscle contraction, Elsevier Smart Health 2018
- Two research assistant positions
available. One is for high-performance machine learning model; the
other is for noisy signal processing. Please contact me if you are
interested.
Project 1-2: Food type inferring
through characterizing mastication dynamics
- This project aims to use wearable motion sensors to sense
mastication dynamics and infer food types accordingly.
- Research skills to learn: feature engineering, classification
algorithms, programming language (Matlab or Python).
- Dataset is available.
- Reference:
S Wang et al., Inferring food types through sensing and
characterizing mastication dynamics, Elsevier Smart Health 2021
- One research assistant position
available. Please contact me if you are interested.
Project 1-3: Chewing side detection
- This project deploys motion sensors on the mastication muscles to
sense muscle bulges and skull vibrations and differentiate chewing
sides accordingly.
- Research skills to learn: deep learning algorithms, signal
processing, programming language (Matlab or Python).
- Dataset is available.
- Reference:
S Wang et al., Wearable Motion Sensor-based Chewing Side Detection,
Elsevier Smart Health 2021
- One research assistant position
available. Please contact me if you are interested.
This topic aims to use wearable sensors to analyze user's walking gait and provide personalized services, such as fall prevention and gait balance analysis.
Project 2-1: Walking surface
detection for fall prevention
- This project uses motion sensors near the ankle to sense
foot-floor friction and recognize walking surfaces.
- Research skills to learn: feature engineering, classification
algorithms, digital signal processing, programming language (Matlab
or Python).
- Dataset is available.
- Reference:
S Wang and G Zhou, Poster: Foot-Floor Friction Based Walking Surface
Detection for Fall Prevention Using Wearable Motion Sensors,
ACM/IEEE CHASE 2023
- One research assistant position
available. Please contact me if you are interested.
This topic aims to analyze user's hand gestures and/or detect hand-device interaction activities using smartphone/wristband.
Project 3-1: CSI-based sign language
recognition
- This project uses CSI information (wireless signals received on
WiFi router) to identify user's sign gestures.
- Research skills to learn: deep learning algorithms (e.g. CNN),
digital signal processing, programming language (Matlab).
- Dataset is available.
- Reference: Y Ma
et al., Signfi: Sign language recognition using wifi, ACM UbiComp
2018
- One research assistant position
available. Please contact me if you are interested.
Project 3-2: Smartphone touchscreen
handwriting recognition
- This project uses smartphone-embedded sensors to recognize the
numbers and characters that user inputs through handwriting. This is
a security-related research topic.
- Research skills to learn: data preprocessing, feature engineering,
machine learning algorithms (e.g. MLP or SVM), digital signal
processing, programming language (Matlab or Python).
- Dataset is available.
- One research assistant position
available. Please contact me if you are interested.
This topic aims to analyze user's hand motions to assess their cognitive capabilities and the trends of improvement or deterioration.
Project 4-1: Cognitive Impairment
Assessment Using Motion Sensor-Embedded Wristbands
- This project uses motion sensor-embedded wristbands to sense
user's hand motions and assess user's cognitive impairment
accordingly.
- Research skills to learn: data preprocessing, feature engineering,
machine learning algorithms, programming language (Python or Matlab).
- One research assistant position
available. Please contact me if you are interested.
If you are interested in other wearable computing and smart health topics (e.g. sports training support, elderly care, etc.), please contact me to have a short discussion.
Please check my Google Scholar page for more references.
I am looking for undergraduate students to work with me on multiple research projects. Interested students are encouraged to contact me.