• Journal of KIISE
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• v.41 no.12
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• pp.1050-1057
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• 2014

Electroencephalogram (EEG)-based brain-computer interfaces (BCI) can be used for a number of purposes in a variety of industries, such as to replace body parts like hands and feet or to improve user convenience. In this paper, we propose a method to decompose and extract motor imagery EEG signal using Empirical Mode Decomposition (EMD) and Fast Fourier Transforms (FFT). The EEG signal classification consists of the following three steps. First, during signal decomposition, the EMD is used to generate Intrinsic Mode Functions (IMFs) from the EEG signal. Then during feature extraction, the power spectral density (PSD) is used to identify the frequency band of the IMFs generated. The FFT is used to extract the features for motor imagery from an IMF that includes mu rhythm. Finally, during classification, the Support Vector Machine (SVM) is used to classify the features of the motor imagery EEG signal. 10-fold cross-validation was then used to estimate the generalization capability of the given classifier., and the results show that the proposed method has an accuracy of 84.50% which is higher than that of other methods.

• Journal of Biomedical Engineering Research
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• v.36 no.6
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• pp.283-290
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• 2015

We proposed blink based online speller for the locked-in syndrome (LIS) patients, paralyzed in nearly all voluntary muscles expect for the eyes, with a simple and easy-to-use eye blink detection glasses. Electrooculogram (EOG) is the golden standard method of eye movement or blink measurement with Ag/AgCl electrodes. However, this method has several drawbacks such as skin irritation and dehydration of conductive gel. To resolve the shortcomings, we used a blink detection system based on a transparent capacitively coupled electrode, which is conductive indium tin oxide (ITO) films. The films make it possible to measure eye blink without direct skin contact and obstruction of field of view. We finally developed user-friendly blink based online speller with the blink detection system. To classify voluntary and non-voluntary blink, we used the double blink for command of the speller. The online speller experiment result with six healthy subjects shows that mean accuracy is 98.96% and letter per minute (LPM) is 4.73, which are better result by comparison with conventional P300 or auditory brain-computer interface (BCI) paradigm. The result of the experiment demonstrates the possibility of applying the proposed system as a communication method for the LIS patients.

• Journal of Biomedical Engineering Research
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• v.39 no.1
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• pp.16-21
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• 2018

In this study, we investigated the activity of Mirror Neuron System(MNS) and Steady State Visual Evoked Potential(SSVEP) according to frequency and duty rate of the flickering action video. Eight subjects were recruited for this study. The stimulus was consisted of a three-minute black and a flickering action video and they were repeatedly presented every six seconds. We used 50%, 75% of duty rate for each frequency 7.5 Hz and 15 Hz, and we also used the non-flickering condition and rest condition. As a result, the Mu suppression was the largest at 7. 5Hz and 50% duty rate and the SSVEP power was higher at 15 Hz than 7.5 Hz.

• Information Systems Review
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• v.19 no.3
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• pp.105-125
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• 2017

Although the relationship between social networking sites (SNS) use and performance has been widely studied, most of these studies have focused on comparing the SNS users' overall performance with that of non-SNS users instead of examining how using SNS midway of a task affects one's task performance. To address this research gap, an experiment was conducted to examine SNS use during a task and its influence on the performance of that task. In this experiment, the role of SNS in various situations was examined by reviewing the literature on break and performance as well as the types of breaks and tasks. Owing to its exploratory nature, this study used various types of data, such as electroencephalography interpretation data generated from a brain-computer interface, self-reported data, and data recorded by a computer. Those participants who used SNS showed an improved performance compared with those who took a short break while doing a simple task. Further analysis showed that the degree of SNS usage and engagement with SNS had positive effects on the participants' simple task performance, while social presence and reassurance of self-worth had negative and positive effects on the participants' complex task performance, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.388-393
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• 2010

Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.