• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.125-154
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• 2009

This paper describes the possibility of human physiological data, especially brain-wave activity, to detect cognitive overload, a phenomenon that may occur while learner uses an e-learning system. If it is found that cognitive overload to be detectable, providing appropriate feedback to learners may be possible. To illustrate the possibility, while engaging in cognitive activities, cognitive load levels were measured by EEG (electroencephalogram) to seek detection of cognitive overload. The task given to learner was a computerized listening and recall test designed to measure working memory capacity, and the test had four progressively increasing degrees of difficulty. Eight male, right-handed, university students were asked to answer 4 sets of tests and each test took from 61 seconds to 198 seconds. A correction ratio was then calculated and EEG results analyzed. The correction ratio of listening and recall tests were 84.5%, 90.6%, 62.5% and 56.3% respectively, and the degree of difficulty had statistical significance. The data highlighted learner cognitive overload on test level of 3 and 4, the higher level tests. Second, the SEF-95% value was greater on test3 and 4 than on tests 1 and 2 indicating that tests 3 and 4 imposed greater cognitive load on participants. Third, the relative power of EEG gamma wave rapidly increased on the 3rd and $4^{th}$ test, and signals from channel F3, F4, C4, F7, and F8 showed statistically significance. These five channels are surrounding the brain's Broca area, and from a brain mapping analysis it was found that F8, right-half of the brain area, was activated relative to the degree of difficulty. Lastly, cross relation analysis showed greater increasing in synchronization at test3 and $4^{th}$ at test1 and 2. From these findings, it is possible to measure brain cognitive load level and cognitive over load via brain activity, which may provide atimely feedback scheme for e-learning systems.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.429-434
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• 2012

This paper presents a technology for manipulating external devices by Brain Computer Interface (BCI) system. Recently, BCI based rehabilitation and assistance system for disabled people, such as patient of Spinal Cord Injury (SCI), general paralysis, and so on, is attracting tremendous interest. Especially, electroencephalogram (EEG) signal is used to organize the BCI system by analyzing the signals, such as evoked potential. The general findings of neurophysiology support an availability of the EEG-based BCI system. We concentrate on the event-related synchronization of motor imagery EEG signal, which have an affinity with an intention for moving control of external device. To analyze the brain activity, short-time Fourier transform and particle swarm optimization are used to optimal feature selection from the preprocessed EEG signals. In our experiment, we can verify that the power spectral density correspond to range mu-rhythm(${\mu}8$~12Hz) have maximum amplitude among the raw signals and most of particles are concentrated in the corresponding region. Result shows accuracy of subject left hand 40% and right hand 38%.

• Sleep Medicine and Psychophysiology
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• v.28 no.2
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• pp.78-85
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• 2021

Objectives: When elderly patients show depressive symptoms, discrimination between depressive disorder and prodromal phase of Alzheimer's disease is important. We tested whether a quantitative electroencephalogram (qEEG) marker was associated with cerebral amyloid-β (Aβ) deposition in older adults with depression. Methods: Non-demented older individuals (≥ 55years) diagnosed with depression were included in the analyses (n = 63; 76.2% female; mean age ± standard deviation 73.7 ± 6.87 years). The participants were divided into Aβ+ (n = 32) and Aβ- (n = 31) groups based on amyloid PET assessment. EEG was recorded during the 7min eye-closed (EC) phase and 3min eye-open (EO) phase, and all EEG data were analyzed using Fourier transform spectral analysis. We tested interaction effects among Aβ positivity, condition (EC vs. EO), laterality (left, midline, or right), and polarity (frontal, central, or posterior) for EEG alpha band power. Then, the EC-to-EO alpha reactivity index (ARI) was examined as a neurophysiological marker for predicting Aβ+ in depressed older adults. Results: The mean power spectral density of the alpha band in EO phase showed a significant difference between the Aβ+ and Aβ- groups (F = 6.258, p = 0.015). A significant 3-way interaction was observed among Aβ positivity, condition, and laterality on alpha-band power after adjusting for age, sex, educational years, global cognitive function, medication use, and white matter hyperintensities on MRI (F = 3.720, p = 0.030). However, post-hoc analyses showed no significant difference in ARI according to Aβ status in any regions of interest. Conclusion: Among older adults with depression, increased power in EO phase alpha band was associated with Aβ positivity. However, EC-to-EO ARI was not confirmed as a predictor for Aβ+ in depressed older individuals. Future studies with larger samples are needed to confirm our results.

• The Journal of Korean Academy of Sensory Integration
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• v.14 no.1
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• pp.19-30
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• 2016

Objective : The purpose of this study was to identify the effects of Interactive Metronome (IM) training on short-term memory and attention for children with mental retardation. Methods : For this study, single-subject experimental research was conducted using an ABA design. We observed two children, twice a week for 9 weeks, which was 18 sessions in total. We evaluated the children's brain waves without intervention and the child's pseudo randomly selected sample of one short-term memory task as assessed in the baseline A phase for three sessions. In the intervention phase the children received 40-50 minutes of Interactive Metronome training twice a week, a total of 12 sessions. The short-term memory test and long form test as assessed after treatment, without brain wave in short form test measuring. During the baseline A phase, data were collected using the same procedure as the baseline A phase. Results : After the interactive metronome training, positive changes was observed in brain waves, attentions and short-term memory. Conclusion : The results of this study expect that IM training has a potential for improving cognitive functions of children with mental retardation. In addition, the results of this study can be used as basic data in attention and short-term memory of occupational therapy intervention for children with mental retardation.

• Journal of Physiology & Pathology in Korean Medicine
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• v.28 no.6
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• pp.674-682
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• 2014

The purpose of this study was to identify the effect of applying oriental music therapy and reliability of electroencephalogram(EEG) equipment. The study was approved by the critical trial judge committee from ${\bigcirc}{\bigcirc}$(IRB No. 2013-07) university. In order to measure test-retest reliability for 15 subjects, EEG for same participants were measured using same method mentioned above after 2 hours from the first measurement. Same provider implemented to each person at same time. Firstly, EEG was measured for 5 minutes after the subject with attached electrodes sat on chair comfortably for 10 minutes. Then, the subject was given mental stress using the four fundamental arithmetic operations for 5 minutes, and measured EEG for another 5 minutes. After that the subject sat on the chair comfortably listening oriental medicine music therapy for 5 minutes, and EEG was measured for 5 minutes again. There was no side effect regarding music therapy reported. Raw data, which was measured in each step, were converted through FFT(fast fourier transform) and analyzed after divided into certain frequency including ${\alpha}$ wave, ${\beta}$ wave, ${\theta}$ wave, immersion wave, stabilization wave, sef100 wave, and sef95 wave. Data were analyzed using wilcoxon signed rank test, Intraclass correlation coefficient(ICC), repeated measures ANOVA with the SPSS program. In test-retes method, there were significantly differences in ${\alpha}$ wave, ${\beta}$ wave, immersion wave, stability wave, ${\theta}$ wave, sef100 wave, sef95 wave. ICC has shown a high degree of reliability that it was ${\alpha}$ wave .877, ${\beta}$ wave .855, ${\gamma}$ wave .895, immersion wave .897, stability wave .816, ${\theta}$ wave .904, sef100 wave .910, sef95 wave .776. Also, there was a statistically significant difference in ${\alpha}$ wave after applying oriental music therapy. Based on these results, it is considered that average of the channel EEG and application of oriental music therapy would be practiced by increase of sample size using this machine.

• Sleep Medicine and Psychophysiology
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• v.5 no.2
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• pp.185-193
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• 1998

Objectives : The hypothesis that the brain is a nonlinear dynamical system exhibiting deterministic chaos has offered new perspectives to the investigation of information processing in the brain of schizophrenic patients. It seemed worthwhile to estimate nonlinear measures of the electroencephalogram (EEG) in positive and negative schizophrenics, because nonlinear measures might serve as indicators of the specific brain function in schizophrenia according to specific psychopathologies. Method : Previous studies which estimated the chaoticity in the brain of schizophrenia with nonlinear methods recorded the EEGs at limited electrodes, so we tried to record EEGs from 16 channels for nonlinear analysis in 8 positive and 9 negative schizophrenics and 8 healthy control subjects. We employed a new method to calculate the nonlinear invariant measures. For limited noisy data, this algorithm was strikingly faster and more accurate than previous ones. Results : Our results showed that the patients with negative schizophrenia had lower the first positive Lyapunov exponents ($L_1$) than the positive schizophrnics and control subjects at $T_3$ lead. Positive symptoms were positively correlated with $L_1$ in $C_3,\;O_1$ leads, and negatively correlated with $C_4$ lead. Conclusion : These results suggest that if clinical variables such as psychopathology or neuroleptic medications would be well controlled, the nonlinear analysis of the EEGs in patients with schizophrenia seems to be a useful tool in analyzing EEG data to explore the neurodynamics.

• Smart Media Journal
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• v.7 no.4
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• pp.106-113
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• 2018

Brand identity (BI) is a key asset that affects consumers' psychological cognition of products and services. In the initial planning stage of the BI design development for a company, a unique approach strategy is required. In the final evaluation stage, a reasonable design evaluation method involving potential consumers needs to be prepared. However, conventional brand identity design evaluation processes tend to depend on the results of surveys, and in many cases it is impossible to be free from the distorting phenomenon of survey respondents' psychological manifestation which is often revealed in the process of the surveys. In this context, this research has explored whether the method of utilizing EEG data of the subjects along with the conventional survey method of preference could be helpful in the process of evaluating the brand identity design. To achieve that, we correlated the subject's preference survey results with the subject's EEG data. 'Attractiveness' and 'concentration' were used as variables. As a result, it was found that there was a high correlation between the results of preference survey on 'attractiveness' and the results of 'EEG' on 'concentration'. Therefore, in addition to the existing conventional qualitative evaluation methods, we confirmed that design evaluation methods using EEG are useful for evaluating tacit knowledge objects such as the BI design.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.134-138
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• 2006

Depression is the most common and widespread mood disorder. About 20% of the population might suffer a major, incapacitating episode of depression during their lifetime. This disorder can be classified into two types: major depressive disorders and bipolar disorder. Since pharmaceutical treatments are different according to types of depression disorders, correct and fast classification is quite critical for depression patients. Yet, classical statistical method, such as minnesota multiphasic personality inventory (MMPI), have some difficulties in applying to depression patients, because the patients suffer from concentration. We used electroencephalogram (EEG) analysis method fer classification of depression. We extracted nonlinearity of information flows between channels and estimated approximate entropy (ApEn) for the EEG at each channel. Using these attributes, we applied two types of data mining classification methods: decision tree and possibilistic support vector machines (PSVM). We found that decision tree showed 85.19% accuracy and PSVM exhibited 77.78% accuracy for classification of depression, 30 patients with major depressive disorder and 24 patients having bipolar disorder.

• Journal of Acupuncture Research
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• v.21 no.4
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• pp.135-147
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• 2004

Objective: Moxibustion is one of major healing technique in oriental medicine. It has been widely used in many disease. There is an text which suggest moxibustion is more efficient to the situation of han(寒) and heo(虛) than yeal(熱) and sil(實) in Huangdineijing <黃帝內經>. The aim of this study is to research the effect of moxibustion at Shinmun(H7) is different according to cold or heat tendendy man by analyzing the electroencephalogram(EEG). Methods: We classified objects by their cold or heat tendency using questionnare for cold - heat patternization. (12 cold tendency man, 19 heat tendency man) Before and after moxibustion at Shinmun(H7), EEG raw data were measured during 5 minutes. The correlation dimension(D2), the correlation dimension variability rate(${\Delta}D2$), largest lyapunov exponent(L1) and largest lyapunov exponent variability rate(${\Delta}L1$) were calculated. We analyzed D2, ${\Delta}D2$, L1, ${\Delta}L1$ to see the effect of moxibustion at Shinmun(H7) was statistically different according to Cold or Heat tendendy man. Results : Paired t-test showed significant differences between before and after moxibustion at Shinmun(H7) on the Fp2 in D2(p<0.05), on the Fp2, F3 and F4 in ${\Delta}L1$(p<0.05). Student Hest showed significant differences between cold and heat tendendy man on the F3 in ${\Delta}L1$(p<0.05). Conclusion: These results suggest that moxibustion at Shinmun has an effect on stabilizing mind and it is more efficient to the cold tendendy man than the heat tendendy man.