Neuromechanics Lab
Clinical Biomechanics, Neuromechanics and Rehabilitation - Mechatronic Tools.
Characterizing, augmenting, and predicting human neuromuscular performance in both healthy individuals and patients with movement disorders.
Force neuromuscular control
− Multi-directional leg rehabilitation for neurological disorders
Diagnostic Flatform
Neuromechanical evaluation
− Optic flow-based evaluation tool for lower extremity changes
− Split-belt adaptation training for post-stroke hemiparetic gait
Optic Flow
Stimuli
Gait Analysis
Aging-in-place rehabilitation
− Resistance exercise & eccentric contraction training
− Audio-visual guided muscle power & proprioception training
Eccentric Contraction
Audio-Visual
Guide
Human-Machine Interface for Bionic Limb
EEG-based Lower-limb Exoskeleton Control
− Selective attention to vibrating stimuli for turning
− Brain-computer interface for lower-limb movements
•Gait imagery for walking, sit/down, and stand up
Brain-Computer Interface
System Overview
EMG-based Bionic Arm Control
− Myoelectric interface for upper-limb movements
− Classification of reaching-to-grasping tasks
• CNN(Convolutional Neural Network)
Myoelectric Interface
Experiment with Amputee
Collaborating with Dr. Lae Hyun Kim, Hyungmin Kim (BCI)
Biosignal Monitoring for Early Diagnosis of Disease
Vibro-tactile Response Analysis for Early Diagnosis for Venous Congestion
− Acceleration and EMG analysis in each stage of deep vein thrombosis (DVT): animal model
− Deep learning-based vibro-tactile EMG classification for early detection toward human’s DVT
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Deep learning (CNN) structure for DVT
