Korea Institute of Science and Technology

Agency for Defense Development

Laehyun Kim

Hyunchul Cho

Da-Hye Kim

Youngjun Kim

Hyung Min Kim

Sung Chul Kang

Hyun Chul Cho

Jung-Woo Lee

Se Hyung Park

Yo-Sub Han

Deukhee Lee

Seung-jun Oh

Song Joo Lee

Seungjae Shin

Jeong Won Cha

Wanjoo Park

Keun Tae Kim

Seul Kee Kim

Sehyung Park

Eon Jo Hong

Kihwan Choi

Jangho Kwon

Jihyeon Ha

Lisa Wiyartanti

Yaeeun Han

Ju-Suk Yun

A method for recognizing blink and eye movement based on electroencephalogram (EEG) and a system thereof are disclosed. The method includes measuring a subject's EEG-based electrooculogram (EOG) signal (hereinafter referred to as 'EOG signal') using three electrodes connected to an EEG head cap. The method further includes performing potential blink detection and zero crossing detection using the EOG signal, and generating a plurality of parameters used for blink and eye movement classification using the EOG signal depending on presence or absence of the potential blink and the zero crossing. In addition, the method further includes classifying the blink and up/down/left/right eye movements of using the plurality of parameters.

Method for recognizing blink and eyeball movement based on EEG and system thereof

Disclosed herein is an image preprocessing/analysis apparatus using machine learning-based artificial intelligence. The image preprocessing apparatus includes a computing system, and the computing system includes: a processor; a communication interface configured to receive an input image; and an artificial neural network configured to generate first and second preprocessing conditions through inference on the input image. The processor includes a first preprocessing module configured to generate a first preprocessed image and a second preprocessing module configured to generate a second preprocessed image. The processor is configured to control the first preprocessing module, the second preprocessing module, the artificial neural network, and the communication interface so that the first preprocessed image and the second preprocessed image are transferred to an image analysis module configured to perform image analysis on the input image based on the first preprocessed image and the second preprocessed image.

Image analysis apparatus using machine learning-based artificial intelligence including preprocessing modules

The present disclosure relates to technology that controls a remote moving body based on collaboration between the moving body and human, and a method for controlling a moving body includes acquiring a first biosignal indicating an intention to start operation of the moving body from a user, operating the moving body, determining a surrounding situation of the moving body that autonomously controls the driving, providing the user with surrounding information of the moving body for inducing path setting, acquiring a second biosignal evoked by recognition of the surrounding information from the user, setting a driving direction of the moving body, commanding the moving body to automatically perform a driving operation to be carried out in the set driving direction, and acquiring a third biosignal responsive to recognition of a driving error from the user and correcting the driving direction of the moving body to induce driving path resetting.

Method for controlling moving body based on collaboration between the moving body and human, and apparatus for controlling the moving body thereof

A biosignal-based avatar control system according to an embodiment of the present disclosure includes an avatar generating unit that generates a user's avatar in a virtual reality environment, a biosignal measuring unit that measures the user's biosignal using a sensor, a command determining unit that determines the user's command based on the measured biosignal, an avatar control unit that controls the avatar to perform the command, an output unit that outputs an image of the avatar in real-time, and a protocol generating unit for generating a protocol that provides predetermined tasks, and determines if the avatar performed the predetermined tasks. According to an embodiment of the present disclosure, it is possible to provide feedback in real-time by understanding the user's intention through analysis of biosignals and controlling the user's avatar in a virtual reality environment, thereby improving the user's brain function and motor function.

Biosignal-based avatar control system and method

The present disclosure relates to technology that controls a robot based on brain-computer interface, and a robot control method acquires a first biosignal indicating an intention to start the operation of the robot from a user to operate the robot, provides the user with visual stimulation of differently set signal cycles corresponding to a plurality of objects for which the robot executes motions, acquires a second biosignal evoked by the visual stimulation from the user to identify an object selected by the user, and acquires a third biosignal corresponding to a motion for the identified object from the user to induce the robot to execute the corresponding motion.

Method for controlling robot based on brain-computer interface and apparatus for controlling meal assistance robot thereof

A method for registering a tooth image with a tooth structure according to an embodiment includes a first registering step for registering a tooth image model obtained from a medical image taken when an object bites a bite including a marker with a bite scanning model obtained by scanning the bite, a second registering step for registering the bite scanning model with a tooth scanning model obtained by scanning a tooth shape of the object, and a third registering step for registering the tooth image model with the tooth scanning model based on the results of the first registering step and the results of the second registering step. As a result, a model including an accurate shape of tooth part difficult to obtain from a medical imaging apparatus can be easily obtained.

Method, apparatus and program for selective registration three-dimensional tooth image data to optical scanning tooth model

A motion control system includes a first capsule robot, which includes a first housing, a first shaft configured to be movable bi-directionally, the first shaft having a first permanent magnet at an outer end, a first leg unit configured to protrude outwards from the first housing, and a first control unit; and a second capsule robot, which includes a second housing, a second shaft configured to be movable bi-directionally, the second shaft having a second permanent magnet at an outer end, a second leg unit, and a second control unit, wherein the first capsule robot is fixed with respect to an the internal organ wall by protruding the first leg unit to the internal organ, and wherein the second capsule robot is connected to the first capsule robot as the first permanent magnet comes into contact with the second permanent magnet by an attractive force.

Motion control system for module type capsule robot in body

A remote control apparatus that provides haptic sensations. The remote control apparatus includes a dial, a motor, a rotary encoder, an encoder counter, a control unit and a motor controller. The remote control apparatus further includes a storage unit, a movement detection unit and a display unit. When a user selects an icon displayed on the display unit by rotating the dial, the control unit interprets the user instruction through the rotary encoder and the encoder counter to control the motor to generate torque for causing a haptic sensation corresponding to the interpreted instruction via the motor controller. While the haptic sensation is conveyed to the user through the dial, the control unit controls an appliance to perform the interpreted instruction thereon.

Remote control apparatus with dialing scheme providing haptic sensations

A method and system for assessing a user reputation and/or a content reliability on contents sharing web sites is provided. In one embodiment, the method includes defining a networked association between users based on social activity information related to the users' social activities on a contents sharing web site, the users' social activities including social activities between the users and/or social activities of the users on the contents sharing web site; obtaining a link relation for at least one of the users based on the networked association; and computing a user reputation for the at least one of the users based on the link relation. The method may further include computing a content reliability of the at least one user-created contents based on the computed user reputation.

Assessment of a user reputation and a content reliability

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Seoul, South Korea

Laehyun Kim