BRAIN-COMPUTER INTERFACE LABORATORY

The Brain-Computer Interface (BCI) Laboratory at Neural & Biomedical Technology Department of Institute for Infocomm Research (I2R) is dedicated to the research and development of neuro-technologies towards various applications aiming at improving, restoring, monitoring, and training neural and cognitive impairments or capabilities.

Core competencies

  • Brain-Computer Interfaces
  • Neural Signal Processing
  • Machine Learning
  • Pattern Recognition

Research focus

  • Algorithms for Electroencephalogram(EEG), Functional Magnetic Resonance Imaging(fMRI), and Functional Near-Infrared Spectrophotometry(fNIRS) analysis, classification, processing
  • Multimodal neural signal processing
  • Signal analysis for neuroscience, cognition, and affection
  • Virtual and real interfaces

Applications

  • Assistive Technology for Communication and Control
  • To enable severely paralyzed people to communicate and interact with the outside world by using a direct brain-computer interface. We focus on systems for communication (speller) and control (wheelchair control), wireless dry EEG, and neural signal decoding, in the framework of non-invasive and invasive BCI.

  • Neuro Rehabilitation for Stroke
  • To provide stroke patients with new rehabilitation systems based on BCI, which guide the patients throughout the rehabilitation training. We focus on the multimodal stroke rehab (ie. to combine BCI with robotics, Virtual Reality(VR), Functional Electrical Stimulation(FES), Transcranial direct current stimulation(tDCS), etc) for upper limb and swallowing rehab, and portable rehabilitation systems.

  • Attention Training and Attention Deficit Hyperactivity Disorder(ADHD) Treatment
  • To provide training and treatment tools for children with ADHD, and systems for human performance measurement and cognitive training.

  • Other Medical and Cognitive Applications
  • To provide methods and systems for epilepsy detection, emotion detection, sleep apnea monitoring and neural informatics (eg, for neural critical care units).

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