• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2575-2581
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• 2011

Recently, systematic research on the brain has been conducted and BCI(Brain -Computer Interface) technology applying electroencephalogram has been actively researched. Especially, serious game technology using BCI device has been the subject of interest. This paper develops a "twosome collaboration dance game," which is a serious game that takes advantage of NeuroSky's SDK(System Development Kit) and helps developing the spirit of team work and sociality based on attention and meditation, unlike existing single player games. We expect that this game will help to visualize brain functions of people and to cure ADHD children and the elderly people with MCI(Mild Cognitive Disorder). It is also expected to play a role of social catalyst to the game culture of the adolescent.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.642-645
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1770-1782
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• 2011

A brain-computer interface (BCI) is a communication system that translates brain activity into commands for computers or other devices. In other words, BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways consisting of nerves and muscles. This is particularly useful for facilitating communication for people suffering from paralysis. Due to the low bit rate, it takes much more time to translate brain activity into commands. Especially it takes much time to input characters by using BCI-based typewriters. In this paper, we propose a brain-operated typewriter which is accelerated by a language prediction model. The proposed system uses three kinds of strategies to improve the entry speed: word completion, next-syllable prediction, and next word prediction. We found that the entry speed of BCI-based typewriter improved about twice as much through our demonstration which utilized the language prediction model.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.153-158
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• 2010

This paper showed the possibilities of performance improvement of Brain-Computer Interface (BCI) decreasing classification error rates of EEG signals by applying Variance-Considered Machine (VCM) which proposed in our previous study. BCI means controlling system such as computer by brain signals. There are many factors which affect performances of BCI. In this paper, we used suggested algorithm as a classification algorithm, the most important factor of the system, and showed the increased correct rates. For the experiments, we used data which are measured during imaginary movements of left hand and foot. The results indicated that superiority of VCM by comparing error rates of the VCM and SVM. We had shown excellence of VCM with theoretical results and simulation results. In this study, superiority of VCM is demonstrated by error rates of real data.

• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.167-171
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• 2007

Brain computer interface is the technology of interface for next generation. Recently, user intention has been tried to be recognized for interfacing a computer. EEG plays important role in developing practical application in this area. Much research has focused on extracting EEG commander generated by human movement. ERD/ERS has generally accepted as important EEG parameters for prediction of human movement. However, There has been difference between initial movement indicated by ERD/ERS and real movement. Therefore, this study was to determine the time differences for brain interface by ERD/ERS. Five university students performed ten repetitive movements. ERD/ERS was determined according to movement execution and the significant pattern showed the difference between movement execution and movement indication of ERD/ERS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.924-926
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• 2015

In this paper, we use the interface, which many countries concentrates research of Brain - Computer Interface with the device and MyndPlay based on the IoT intelligent Arduino. Finally we will make the Brain - Computer Connection environment, the purpose of Brain - Computer Interface. Recognizes the EEG of a person who wearing the equipment, analyze, classify, and we did a research to design an intelligent thing to suit user's condition. In addition, we use the XBee, and Bluetooth to communicate to other devices, such as smart phone. In conclusion, this paper check users current status via brain waves, and it allows to control the power and other objects by using the EEG(Electroencephalography).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.943-944
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.46.3-46
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• 2001

The overall aim of this research is to develop a computer communication interface based on brain-wave bio potentials for physically disabled people. The work focuses on using EOG and EMG signals to input characters one by one using cursor movements on a GUI screen. The Cyberlink TM system is used to acquire brain waves in real time with electrodes. EMG and EOG signals are used to direct a cursor in order to select, or to click on a character on the screen. We present a novel method for automatic EOG pattern detection by using wavelet transforms with a neuro-fuzzy approach ...

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.605-610
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• 2008

There are many methods for Human-Computer Interface. Recently, many researchers are studying about Brain-Signal this is because not only the disabled can use a computer by their thought without their limbs but also it is convenient to general people. But, studies about it are early stages. This paper proposes an EEG signals measurement and analysis methods for Brain-Computer Interface. Our purpose of this research is recognition of subject's intention when they imagine moving their arms. EEG signals are recorded during imaginary movement of subject's arms at electrode positions Fp1, Fp2, C3, C4. We made an analysis ERS(Event-Related Synchronization) and ERD(Event-Related Desynchronization) which are detected when people move their limbs in the ${\mu}$ waves and ${\beta}$ waves. Results of this research showed that ${\mu}$ waves are decreased and ${\beta}$ waves are increased at left brain during the imaginary movement of right hand. In contrast, ${\mu}$ waves are decreased and ${\beta}$ waves are increased at right brain during the imaginary movement of left hand.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.427-432
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• 2003

EEG is an electrical signal, which occurs during information processing in the brain. These EEG signals have been used clinically, but nowadays we ate mainly studying Brain-Computer Interface (BCI) such as interfacing with a computer through the EEG, controlling the machine through the EEG. The ultimate purpose of BCI study is specifying the EEG at various mental states so as to control the computer and machine. This research makes the controlling system of directions with the artifact that are generated from the subject s will, for the purpose of controlling the machine correctly and reliably We made the system like this. First, we select the particular artifact among the EEG mixed with artifact, then, recognize and classify the signals pattern, then, change the signals to general signals that can be used by the controlling system of directions.