Objectives
Neuroplasticity in cell-based stroke model
Understanding the effect of rehabilitation on neuroplasticity based on a cell
- based stroke model Measurement and analysis of electrophysiological signals during rehabilitation, and setting the electrical stimulation conditions for cells
- Platform design to stably apply electrical stimulation to cellular stroke model
- Investigation of the effects of electrical stimulation on neuroplasticity-related gene/protein of cells
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_0-1024x248.png)
Computational modeling to predict a rehabilitation outcome
We are developing a computational model to predict a patient’s rehabilitation outcomes based on brain motor network analysis.
- Motor learning network analysis
- Building a computational model for motor learning
- Constructing a rehabilitation predictor based on the motor learning model.
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_2.png)
Brain-machine interface for high-effective rehabilitation
We are constructing a brain-machine interface system that reflects a patient’s motor intention to increase the patient’s active participation in rehabilitation sessions.
- Feature extraction for motor intention
- Building motor intention classifier using real-time EEG
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_1.png)
Precision intention recognition – HD-sEMG based interface for Electromyography
Developing a robust motion intention recognition algorithm for the electrode position change, by stochastic signal decomposition
- Extraction of independent muscle unit signal
- Compensation algorithm for electrode position change
- Movement intention recognition system which is capable of distinguish external forces from users’ internal and forces by rehabilitation equipment
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_9.png)
Compensating fatigue effect on muscle synergy
Developing a method to compensate fatigue effects during long-term exercise
- Examining muscle synergy difference due to muscle fatigue during long-term exercise of normal people
- Distinguish signal changes due to factors other than active muscles during long term exercise
- Examine the correlation between long-term muscle fatigue and muscle synergy by analyzing collected EMG signals
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_3-1024x231.png)
Upper limb muscle synergy model for patients with neurological disorders
Extraction, classification and analysis of upper limb muscle synergy model.
- Extraction of upper limb muscle synergy model from high-density EMG
- Study of correlation between characteristics of each patient’s synergy model and motor function
- Building a robot-based rehabilitation strategy based on change in upper limb synergy model
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_6-1024x213.png)
Take-home rehabilitation monitoring using wearable device
Developing home-based rehabilitation monitoring system using minimal IMUs
- Real-time upper-limb activities classification using machine learning
- Estimating upper limb kinematics and kinetics from minimal IMUs
- Extract take-home rehabilitation indicators from IMUs
- Construct data base of take-home rehabilitation
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_4-1024x407.png)
High DOF soft wearable device & control
Developing highly dexterous soft wearable glove capable of conducting challenging hand manipulation for patients with severe hand impairment.
- Designing soft wearable robotic glove with robust & flexible actuation
- BMI for recognizing dexterous finger/thumb movement intention
- Intelligent shared control of high DOF soft wearable glove
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_5.png)
Custom intelligent soft wearable structure
Developing an intelligent soft wearable structure based on patient information to provide optimal assistive power and fit in daily life.
- Development of intelligent soft wearable structure based on patient joint stiffness measurement information
- Development and implementation of non-linear controller to assist user according to target stiffness
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_8-1024x262.png)
Sensory feedback and selective electrical stimulation system
Developing vibration and electrical stimulation system capable of propriception stimulation in appropriate areas and reducing stiffness and muscle tension.
- Development of a system that can simultaneously use muscle stimulation and nerve blocking
- Determine optimal electrode position and stimulation signal
- Integrating with the brain-robot interface and intention recognition system (EEG and large-area sEMG) to operate stroke patients
![](http://renew.kaist.ac.kr/wp-content/uploads/sites/2/2020/03/objective_7-1024x571.png)