• Modal Analysis - driven Gaussian Process for a Gait Parameters Estimation and Individuals' classification from CCTV and smartphone camera footages

Develop a machine learning model trained with gait parameters from CCTV (OpenPose-based), MCC, and IMU sensors, incorporating body measurements, age, and gender. Process video footage to analyze gait and correct parameters to match MCC or IMU measurements, enabling precise gait analysis in indoor and outdoor environments. 

• Development of Foot Diagnosis and Shoe Manufacturing Technology for Disabled

Develop 3D scanning technology for digitizing and analyzing foot morphology. Advance plantar surface stiffness measurement, establish diagnostic indicators, and enhance foot assessment models. Utilize finite element analysis (FEA) to study foot deformation and stress distribution for more accurate health assessments. 

• Development of edge computing-based pressure ulcer prevention ultra-low noise type posture change care robot compatible with care devices

We develop air-cell mattress technology to reduce pressure on ulcer-prone areas and integrate sensor-vision data processing with deep learning. Our research focuses on predicting pressure ulcer risk through advanced algorithms and optimizing posture adjustments to minimize pressure in vulnerable regions.

• Public distribution through a One-Stop solution with localization of certified electronic-controlled hydraulic knee prosthesis, including clinical study and empirical platform systems

This project aims to develop a one-stop solution for the public distribution of hydraulic microprocessor knees (MPKs), integrating hydraulic MPK development, domestic certification system development, and clinical and real-world evaluation. Our laboratory quantitatively and qualitatively evaluates prosthesis usability in a living-lab environment based on daily-life and gait scenarios and conducts detailed gait analyses of transfemoral amputees.

• Prediction of Diabetic Ulcer and Stiffness of the Soft Tissue of Foot Using Indentation Device 

Our research studies plantar soft tissue changes influenced by biomechanical and pathological factors, particularly in relation to diabetes and abnormal foot pressure. Using a custom indentation device, we analyze tissue mechanics and pressure distribution to predict diabetic ulceration risk. Currently, we are developing AI models to estimate plantar tissue stiffness from gait characteristics, aiming to differentiate stiffness changes caused by pathology versus epidemiological factors 

• Structure Analysis and Optimum Design for Smart Shoulder Joint Exerciser 

Lightweight and compact smart shoulder joint exerciser frame through topology optimization technique; Analysis of smart shoulder joint exerciser kinematics according to human body dimensions and training patterns (Flexion/extension, adduction/abduction, horizontal adduction/horizontal abduction); Kinematic characteristics and feasibility validation for developed smart shoulder exerciser. 

• Development of Power Assist Devices for Wheelchair Users 

Analysis of complements for detachable power assistance devices for wheelchair; Analysis for changes in center of gravity and system vibration analysis according to terrain and occupant posture; Operation controller interface design analysis; Analysis and application of product design and interface complements.