Osong Medical Innovation Foundation, Korea University Research and Business Foundation

Seong-Whan Lee

Ji-Hoon Jeong

No-Sang Kwak

Seo-Hyun Lee

Byeong-hoo Lee

Minji Lee

Keun-Tae Kim

Ji-Yong Kim

Chae Bin Song

Do-Yeun Lee

No Sang Kwak

Young-Eun Lee

Byoung-Hee Kwon

Kyung-Hwan Shim

One embodiment of the user authentication method using brainwave signal according to imagined speech includes extracting and storing characteristic information of a first brainwave signal generated by an imagined speech of a first user based on preset imagined speech induction information provided to the first user by the user authentication apparatus, and determining whether a second user matches the first user by extracting characteristic information of a second brainwave signal generated by an imagined speech of the second user, based on preset imagined speech induction information provided to the second user, comparing the characteristic information of the first brainwave signal with the characteristic information of the second brainwave signal stored according to the extracting and storing, and analyzing a result of the comparing by the user authentication apparatus.

User authentication apparatus and method using brainwave signal according to imagined speech

Provided is a brain-machine interface based intention determination device using a virtual environment, including: an input unit that receives a control mode; a training output unit that outputs training information; a collection unit that collects a brain signal; a first preprocessing unit that extracts time-frequency information; a second preprocessing unit that generates physical information; a learning unit that learns control information according to a pattern of physical information; a determination unit that determines control information; and a command output unit that outputs a control command matching the control information.

Brain-machine interface based intention determination device and method using virtual environment

The present invention relates to a brain-computer interface system and a method for recognizing a conversation intention of a user using the same in addition to inferring the waveform of word sound intended by a user from an imagined speech brainwave associated with a word intended by a user, since the user can intuitively recognize the sentence he/she wants to speak through the imagined speech by classifying words that are most relevant to the imagined speech brainwave of the user in a database in which a word often used by the user or frequently used in a specific situation is stored and by generating a sentence intended by the user by recognizing the words classified in this way, it is possible to perform communication by only thoughts of the user.

Brain-computer interface system and method for recognizing conversation intention of user using the same

A semi-dry electrode for recording an electroencephalogram, includes an outer membrane that forms an electrode contact surface with a predetermined area contacting a scalp; an electrode body that is connected to an edge of the outer membrane and forms an internal space into which an electrolyte solution is filled; and an electrical conductor sensor that is located inside the electrode body and measures an ion current transmitted through the outer membrane. The outer membrane has a plurality of fine holes and holes that are larger than the fine holes.

Membrane based semi-dry electrode for recording electroencephalogram

Provided is a smart control device including: a collection unit that collects a brain signal generated from a visual stimulus for color; a preprocessing unit that extracts pattern information from the brain signal; a selection unit that selects reference information having the highest correlation by comparing the pattern information to reference information provided in advance; and a control unit that has control commands set in advance and executes the control command matching the selected reference information.

Smart control device for determining user's intention from color stimulus based on brain-computer interface and control method thereof

Brain-computer interface system and method for decoding user's conversation intention using the same

The method for inducing sleep by a sleep inducing system includes acquiring brain signals of a user as sleeping time passes; calculating a functional connectivity value between two channels for each frequency based on the acquired brain signals and performing brain network analysis; determining the stage of sleep of the user based on features of the analyzed brain network; determining a target frequency according to the determined stage of sleep and generating a binaural beat with which the brain signals of the user are induced to the target frequency; combining the generated binaural beat with ASMR information; providing the combined auditory stimulus information to the user; and determining whether the current stage of sleep of the user is maintained at an appropriate proportion with respect to total sleep time, determining whether or not to induce the next stage of sleep, and performing feedback according to the result of determination.

Method and system for inducing sleep

A method of monitoring an anesthesia and consciousness depth through brain network analysis by a computing device according to the present disclosure includes: acquiring a user's brain signals extracted during anesthesia; performing pre-treatment to the acquired brain signals to be suitable for brain network analysis; calculating a functional connectivity value between two channels for each frequency based on the pre-treated brain signals and performing brain network analysis; determining an anesthesia and consciousness depth of the user based on features of the analyzed brain network; and providing the determined anesthesia and consciousness depth of the user through a user interface.

Method and apparatus of monitoring anaesthesia and consciousness depth through brain network analysis

The present disclosure provides a method of generating a control signal to control a motion of a robot arm device by a brain-computer interface (BCI) apparatus and the BCI apparatus. The present method includes: measuring a first electroencephalogram (EEG) and extracting an abstract feature of the first EEG; determining one of a reaching control mode, a hand grasp/opening control mode, and a wrist rotation control mode based on the abstract feature of the first EEG; performing feedback of the determined control mode to a user; measuring an error-related potential as a second EEG; redetermining the control mode by re-extracting an abstract feature of the first EEG when the error-related potential exceeds a threshold value or measuring a third EEG when the error-related potential does not exceed the threshold value; extracting a result value by applying different feature extraction methods and different classification methods to the third EEG depending on the determined control mode; and supplying a control signal generated based on the result value to the robot arm device.

Brain computer interface (BCI) apparatus and method of generating control signal by BCI apparatus

An exemplary embodiment of the present disclosure provides a method of recognizing, by a controller, an intention of a user who wears a head mounted display to which electroencephalogram electrodes are attached. The method includes obtaining brain signals for learning from each of the head mounted display and an additional electrode device coupled to the head mounted display, in a state where a training image causing brain signals is displayed on the head mounted display; learning a first relational model between electrodes of the head mounted display and electrodes of the additional electrode device using the brain signals for learning; measuring brain signals by the head mounted display decoupled with the additional electrode device, in a state where a specific image is displayed on the head mounted display; estimating brain signals of the additional electrode device non-measured, from the brain signals measured by the head mounted display based on the first relational model; and recognizing a user intention corresponding to the measured brain signals and the estimated brain signals.

Method of recognizing user intention by estimating brain signals, and brain-computer interface apparatus based on head mounted display implementing the method

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Seoul, South Korea

Seong-Whan Lee