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Center for Intelligent Team Robotics & Human-Robot Collaboration

Robot Decision & Control

Li-Wei Ko Professor

Li-Wei Ko

Research Field

Neural Engineering; Brain-Computer Interfaces(BCI); AI and Machine Learning for Medical Data Mining; Artificial Intelligence and Machine Learning for Biomedical Signal Processing; Computational Neuroscience; Neural Networks and Neuro-fuzzy Systems; Intelligent Healthcare Systems

Education

Ph.D., Institute of Electrical and Control Engineering, National Chiao Tung University

Lab

Neural Engineering Lab

Website

https://neuroengineering.lab.nycu.edu.tw/

Application Fields

  • Stroke Rehabilitation: Supports lower-limb recovery in stroke patients through BCI- and exoskeleton-assisted gait training.
  • Neurorehabilitation and Mobility Training: Assists patients with neurological injury, degenerative diseases, or reduced mobility in standing, walking, balance, and coordination training.
  • Smart Rehabilitation Services: Enables safe, standardized, and personalized gait training in hospitals and rehabilitation centers.
  • Elderly Care and Long-Term Rehabilitation: Provides intelligent and active lower-limb rehabilitation support for aging-related mobility decline.
Technology Available for Transfer

  • EEG Decoding Algorithm: Extracts and classifies EEG features for lower-limb motor intention, serving as a core module for BCI exoskeletons and neurorehabilitation systems.
  • Non-Invasive Wireless BCI Module: Acquires brain signals through a wearable wireless BCI to support real-time signal analysis and control in rehabilitation settings.
  • BCI-Based Exoskeleton Control Interface: Converts EEG decoding outputs into exoskeleton control signals for gait initiation, walking training, and rehabilitation control.
Technology in Development

  • Closed-Loop BCI Lower-Limb Exoskeleton Rehabilitation System: Integrates EEG signals, AI decoding, exoskeleton control, and feedback for active rehabilitation.
  • Multi-Stage Personalized Rehabilitation Platform: Supports natural walking and BCI-based training according to patients’ recovery status.
  • Clinical Validation and Smart Healthcare Deployment: Plans future clinical validation and continuous optimization for improved clinical feasibility.
Contact

Faculty Webpage: Webpage

Laboratory: Neural Engineering Lab