• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.832-837
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• 2007

Many researchers are studying brain activity to using functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG), and etc. They are used detection of seizures or epilepsy and deception detection in the main. In this paper, we focus on emotion recognition by recording brain waves. We specially use fMRI, TRS, and EEG for measuring brain activity Researchers are experimenting brain waves to get only a measuring apparatus or to use both fMRI and EEG. This paper is measured that we take images of fMRI and TRS about brain activity as human emotions and then we take data of EEG signals. Especially, we focus on EEG signals analysis. We analyze not only original features in brain waves but also transferred features to classify into five sections as frequency. And we eliminate low frequency from 0.2 to 4Hz for EEG artifacts elimination.

• 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 KIISE:Software and Applications
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• v.35 no.3
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• pp.169-178
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• 2008

Cancer patients have been suffered from the instability of mind/body and unbalanced homeostasis because of cancer progression and medical treatment such as chemotherapy, It is very important that appropriated actions can be promptly taken by monitoring cancer patients' mental conditions. For this reason, it is crucial to develop a monitoring method which is convenient and not harmful to their body. Brain-computer-interface(BCI) system is introduced for the purpose in this paper. Prefrontal brain waves of cancer patients and control groups have been measured by a portable neurofeedback(NF) system based on self-regulation of the human electroencephalogram(EEG). The NF system consists of the portable EEG amplifier and a headband with dry electrodes placed on Fp1 and Fp2 sites. Patterns of the prefrontal brain waves taken by computer are correlated to brain quotients by EEG-analysis program. Basic rhythm quotient, attention quotient, emotional quotient, anti-stress quotient and correlation quotient of control group have shown high significant level compared with the cancer patients group. On the other hand, the EEG patterns analysis is shown its possibility to be an important methodology of monitoring cancer patients' condition.

• Journal of Haehwa Medicine
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• v.10 no.1
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• pp.365-374
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• 2001

The brain is one of the most complex systems in nature. Brain waves, or the "EEG", are electrical signals that can be recorded from the brain, either directly or through the scalp. The kind of brain wave recorded depends on the behavior of the animal, and is the visible evidence of the kind of neuronal (brain cell) processing necessary for that behavior. But, EEG had been considered as a virtually infinite-dimensional random signal. However, nonlinear dynamics light on dynamical aspects of the human EEG. The methods of nonlinear dynamics provide excellent tolls for the study of multi-variable, complex system such as EEG. In this study, 20 persons seperated in 2 groups were examined with EEG, one group stimulated on specific area of the sole of the foot with footbed inside the shoes. This experiment resulted in at the group stimulated on specific area of the sole of the foot correlation dimension of P4 and O1 channels increased significantly. Therefore. we obserbed that stimulation on specific area of the body had a constant effections on the specific channels.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.589-594
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• 2014

It has been known that the particular brain waves are induced when a human concentrates. In our study, we aimed to analysis the brain waves related to human concentration using visual stimulus to induce the concentration. The visual stimulus tasks were presented to subjects for concentration. We measured EEG signals with several channels and analyzed the signals into several frequency bands. In the measured EEG signals, we analyzed to focus on theta waves, SMR waves and mid-beta waves. Therefore we presented the results to investigate characteristics of the EEG signals related to the human concentration.

• The Mathematical Education
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• v.55 no.3
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• pp.383-396
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• 2016

This study investigated highschool students' brain waves on functional tasks such as a transition(F task) from equation to graph and the other transition(G task) vice versa. A total of 39 students participated in the study who attended a high school located in Gyunggi province. These students were divided into two groups, HMA and LMA by MASS test revised by Ko, & Yi (2012). The functional tasks for the stroop task to measure EEG were provided from a previous study, Seok(2015). The results indicated two groups on G tasks showed deeper and wider brain waves which demonstrated G tasks were more difficult than F tasks. However, HMA group had an effect of the non-psychological program which had given more chances on G tasks rather than F tasks within Students' Zone of Proximal Development. Also, HMA group's brain waves had more ranges in amplitude and width of waves. These results imply that the characteristics of students' brain waves with math anxiety are consistent to the previous studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.170-174
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• 2007

Although research efforts for brain waves have prospered in medicine and engineering, acupuncture still has a long way to go regarding researches on brain waves analysis. Thus this study set out to analyze brain waves stimulated by indirect mugwort moxibustion, which was part of acupuncture techniques, and to investigate their correlations with the automatic nervous system. For the experiments, stimulation was given to Jungwan, Shingwol and Gwanwon, which were some of the spots on the body suitable for acupuncture, through indirect mugwort moxibustion. The subjects' brain waves were measured before the stimulation, during the stimulation, and one hour and two hours after the stimulation. The measurements were analyzed with Matlab 7.0 for FFT and frequency power spectrum. Then the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves were analyzed and examined for changes to the percentage of each frequency and to the amplitude of vibration according to the stages of stimulation. The EEG data of the entire brain were translated into FFT to analyze the percentage of the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves. As a result, the ${\alpha}$ waves recorded a double increase after the stimulation. The power spectrum analysis results of the entire brain decreased the ${\alpha}$ and ${\beta}$ waves dropping in the energy level, which suggested that the parasympathetic nerves were activated. When the results of the study were compared with those of the previous study, it's confirmed that indirect moxibustion stimulation could cause changes to the automatic nervous system and bring stability to those who were nervous or under stress due to the proportionate increase of the ${\alpha}$ waves.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.129-135
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• 2018

In this study, we designed a model that can measure the level of user's concentration by measuring and analyzing EEG data of the subjects who are performing Continuous Performance Test based on visual stimulus. This study focused on alpha and beta waves, which are closely related to concentration in various brain waves. There are a lot of research and services to enhance not only concentration but also brain activity. However, there are formidable barriers to ordinary people for using routinely because of high cost and complex procedures. Therefore, this study designed the model using the portable EEG measurement device with reasonable cost and Visual Continuous Performance Test which we developed as a simplified version of the existing CPT. This study aims to measure the concentration level of the subject objectively through simple and affordable way, EEG analysis. Concentration is also closely related to various brain diseases such as dementia, depression, and ADHD. Therefore, we believe that our proposed model can be useful not only for improving concentration but also brain disease prediction and monitoring research. In addition, the combination of this model and the Brain Computer Interface technology can create greater synergy in various fields.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.315-330
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• 2012

Recently, methodologies for developing brain-computer interface (BCI) games using the BCI have been actively researched. The existing general framework for processing brain waves does not provide the functions required to develop BCI games. Thus, developing BCI games is difficult and requires a large amount of time. Effective BCI game development requires a BCI game framework. Therefore the BCI game framework should provide the functions to generate discrete values, events, and converted waves considering the difference between the brain waves of users and the BCIs of those. In this paper, BCI game frameworks for processing brain waves for BCI games are proposed. A variety of processes for converting brain waves to apply the measured brain waves to the games are also proposed. In an experiment the frameworks proposed were applied to a BCI game for visual perception training. Furthermore, it was verified that the time required for BCI game development was reduced when the framework proposed in the experiment was applied.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.4
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• pp.440-454
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• 2014

This study examined the wearing effect of 3D compression suits on quantitative electroencephalogram (EEG) during walking and rest. Ten males in their 20s wore three types of experimental clothing, a loose-fit wear (BS), a 3D compression suit (3D CS), and a power film welded on CS (3D WCS); in addition, EEG signals were measured during resting, walking, after walking, and after sit-ups. The results showed that a higher pressure (due to 3D CS and 3D WCS) increased the 'Concentration' level and the 'Cognitive load' of brain waves during treadmill walking due to a higher cortex activity level when walking. Differentiation was shown between two compression suits and BS was enhanced during walking on a treadmill; however, the brain waves of 'Relaxation' between two compression suits were significantly different after walking, i.e., 'Relaxation' level of 3D WCS was the highest. Rigorous exercise such as sit-ups was inefficient to distinguish the effect of compression suits on EEG. Participants perceived a higher pressure due to compression suits; however, the wear comfort of two compression suits was maintained. Two compression suits were rated as supportive and helpful during walking. Various EEG parameters such as the indices of 'Relaxation', 'Concentration' and 'Cognitive load' were effective to observe the effect of 3D compression suits on wearers' brain waves during and after walking.