Welcome to BCI LAB!
We develop innovative BCI technologies that link the brain and the digital world. Our research drives innovation in neural signal processing, machine learning, and human-computer interaction, empowering seamless communication and control.
Join us in shaping the next generation of brain-computer interfaces.
Brain-Computer Interface (BCI) is a technology that enables direct communication between the brain and external devices by translating neural activity into digital commands. BCIs allow users to control computers, prosthetic limbs, or assistive devices without physical movement, making them particularly beneficial for individuals with motor impairments. At the same time, BCI applications are expanding beyond clinical use to enhance human-computer interaction for the general public, including brain-controlled gaming, cognitive enhancement, and seamless interaction with smart environments.
At BCI LAB, we focus on advancing BCI technology not only for assistive applications but also for broader digital healthcare innovations. Our research explores how brain activity can be utilized for mental health monitoring, and cognitive state analysis, ultimately contributing to the development of next-generation neurotechnology for both patients and the general public.
The P300 is a cognitive event-related potential (ERP) that occurs approximately 300 milliseconds after the presentation of a rare or significant stimulus. It reflects the brain’s recognition and evaluation of external stimuli, making it a reliable neural marker for detecting user intention and cognitive responses. Our lab conducts a wide range of applied research utilizing the P300 signal with non-invasive EEG systems, exploring its potential in real-time communication, control, and immersive interaction technologies.
Our representative research areas include:
BCI Speller
We develop P300-based speller systems that allow users to communicate by selecting characters through visual stimuli. This technology is particularly beneficial for individuals with motor disabilities, and our research aims to enhance the accuracy, speed, and usability of the system.
World Tour System (WTS)
This system enables users to explore virtual travel destinations using P300 signals. By selecting visually presented options through brain responses, users can take a cognitive-driven "tour" experience.
BCI Drone
We are developing systems that allow users to control drones using P300 responses. By detecting user commands from EEG signals in real time, we aim to build reliable and responsive drone interfaces that can be used in various applications, including assistive technology and remote operations.
The Motor Imagery (MI) refers to the mental simulation of movement without actual muscle activity, and it can be used to control external devices solely through imagination. Our goal is to develop MI-BCI systems that enable intuitive and hands-free control of various technologies.
Our lab is dedicated to advancing digital healthcare solutions by leveraging physiological signals and machine learning techniques to support diagnosis, monitoring, and treatment. We aim to enhance personal health and the quality of medical care by developing non-invasive systems that utilize various physiological signals. These systems are designed to be applicable in both clinical and everyday environments, contributing to more accessible and effective digital healthcare solutions.
Our representative research topics include:
Blood pressure monitoring
For continuous, cuffless monitoring, Blood pressure prediction uses photoplethysmography (PPG) signals.
Sleep Stage Prediction
Sleep stage classification using EEG signals to analyze and improve sleep quality.
Mobile application development for quantitatively assessing motor symptoms in patients with Parkinson’s disease and essential tremor, supporting clinical diagnosis and treatment planning.
Our lab also explores neurofeedback and neuromodulation techniques to enhance cognitive functions and self-regulation through brain activity monitoring and feedback. We aim to develop intuitive and engaging applications that utilize real-time EEG signals, with the goal of promoting mental wellness and improving cognitive performance in daily life.
Developed the “MindCar” system, a concentration-based racing game that uses EEG signals from commercial brainwave devices to control vehicle speed based on the user's attention level.
Our lab also develops serious games powered by EEG to promote cognitive enhancement and mental health. These games are designed not just for entertainment, but to provide meaningful therapeutic or educational value through brainwave-based interaction and feedback.
Our representative research topics include:
Development of attention-enhancing EEG games to improve users’ concentration through neurofeedback mechanisms.
Design of EEG-based games for individuals with depression, aiming to support emotional regulation and mental well-being.
Our lab actively investigates the application of deep learning and machine learning techniques in neuroscience to improve the performance and practicality of BCI systems. We explore cutting-edge models and data-driven approaches to enhance signal interpretation, reduce user burden, and expand clinical applications.
Our representative research topics include:
Generative EEG modeling to synthesize brain signals and reduce calibration sessions using productive model-based approaches.
Development of Transformer-based neural networks for improved accuracy and robustness in EEG decoding.
Application of machine learning algorithms to analyze clinical datasets for neurological disorder research and diagnostic support.
At BCI Lab, we conduct cutting-edge research in neuroscience, cognitive science, and brain-computer interfaces, bridging fundamental brain research with real-world applications.
Our lab thrives with passionate undergraduate, master's, and PhD students actively engaging in innovative research. If you're eager to explore brain science and neuroengineering, join us in shaping the future!