Resaerch Project


We develop smart/wearable assistive technologies (ATs) for promoting independence for people with disabilities.

Multifunctional intraORal Assistive technology (MORA)

Development of new concept of intra-oral assistive technology for people with high-level spinal cord injuries. We analyze the performance using MORA for various realistic conditions for activities of daily living.

“we designed and tested a tracer-free tongue-controlled AT based on multiple contact-based optical distance sensors, ambient light sensor, and multi-sensor data fusion algorithm. This new AT will address the Midas touch problem while retaining advantages of the contact-based approach.”

“we develop the wearable tracer-free tongue-controlled assistive technology, MORA, that can be utilized with the multifunctional feature using a custom designed wireless wheelchair interface via a smartphone app."

“We designed the Fitts' law and Steering law based tasks on the computer, wheelchair, and virtual reality to evaluate the performance of the users.”


Funded by Department of Veterans Affairs, Specially Adapted Housing Assistive Technology (SAHAT) and National Science Foundation (NSF: 1948503)

Wearable Neuromodulation (Periperal Nerve Stimulation)

We have developed a wireless wearable stimulation system that analyzes upper limb tremor using a three-axis accelerometer and that modulates/attenuates tremor using peripheral-nerve electrical stimulation with adjustable stimulation parameters and a real-time tremor detection algorithm.

“Actual experimental setup for the bean transfer tasks: One of the subjects performed the bean-transfer task while wearing the wrist device and electrodes..”

We are currently working on the parameter optimization of the upper-limb neuromodulation to subside the tremor movement in real time.

We are currently working on the parameter optimization of the upper-limb neuromodulation to subside the tremor movement in real time.


Funded by Texas A&M University, The College of Engineering and the College of Education and Human Development Seed Grant

In-home Mobile Diagnosis System

We approach to develop the home-based clinical evaluation based on the quantitative functional performance and tremor metrics during the activities of daily living (ADLs) in the long term.

"We analyzed performance metrics such as completion time, outside area, path efficiency, throughput, and length of the actual traces for the three computer-based tasks and correlated them to the clinical evaluation (TETRAS) and tremor metrics (frequency and power of tremor). The performance metrics of the computer-based assessment tasks showed highly correlated linear regression models with tremor power (severity). With this information, we evaluated the feasibility of the new quantitative assessment method capable of accurately predicting metrics based on the characteristics of tremor movements."

"To expand in-home tremor assessment, we develop the VR based task setup that can extract the pathological characteristics while they perform some ADL tasks in VR environment. "

Real-time AI-based Magnetic Anomaly Detection System

To minimize the excavation damage of underground pipelines, we propose to provide real-time feedback to operators by monitoring the distance information from the underground pipeline. Despite multiple efforts to locate underground ferromagnetic pipelines using the magnetic anomaly detection, it has not been implemented in real-time excavation operations due to low signal-to-noise ratios, unknown external magnetic interference, and high computational power. To address these limitations, we propose an approach to locating a custom-designed wireless sensor system on the excavator bucket to increase accuracy of real-time distance estimation with efficient external magnetic interference cancellation.


Funded by “FW-HTF-RM: The Future of Teleoperation in Construction Workplaces” National Science Foundation, Future of Work at the Human-Technology Frontier: Core Research and “NRI: Human-robot Interface for Extraterrestrial Construction,” National Science Foundation.