• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2548-2554
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• 2010

This paper describes a design of fast Fourier transform(FFT) processor for EEG(electroencephalogram) signal analysis for health care services. Hamming window function with 1/2 overlapping is adopted to perform short-time FFT(ST-FFT) of a long period EEG signal occurred in real-time. In order to analyze efficiently EEG signals which have frequency characteristics in the range of 0 Hz to 100 Hz, a 256-point FFT processor is designed, which is based on a single-memory bank architecture and the radix-4 algorithm. The designed FFT processor has been verified by FPGA implementation, and has high accuracy with arithmetic error less than 2%.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.57-62
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• 1998

The objectice of this study is to dvaluate the physical condition response of a drever by the change of CO$^{2}$ concentration in the automobile with EEG spectrum analysis. The experiment was performed in a semi-shielded simulated automobile with 10 healthy adults. The results showed that as CO$_{2}$ concentration increased from 500ppm to 6,000ppm, the $\alpha$' value significantly decreased(p*<0.05) while $\beta$' increased (p*<0.05). In a real parked automobile with 2 adult passengers, the CO$_{2}$ gas concintration reached at 6,000ppm in 15 minutes. These spectral data are in well agreement with the subject's verval statement of experiencing uncomfortableness when CO$_{2}$gas was increased ti over 5,000ppm. These results indecated that the EEG spectrum analysis can be appropriately used to assess physical condition of a driver in the changing automobile environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.88-91
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• 2010

This paper describes a design of fast Fourier transform(FFT) processor for EEG(electroencephalogram) signal analysis for health care services. Hamming window function with 1/2 overlapping is adopted to perform short-time FFT(ST-FFT) of a long period EEG signal occurred in real-time. In order to analyze efficiently EEG signals which have frequency characteristics in the range of 0 Hz to 100 Hz, a 256-point FFT processor based on single-memory bank architecture and radix-4 algorithm is designed. The designed FFT processor has high accuracy with arithmetic error less than 3%.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.451-456
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• 2014

The correlations between electroencephalographic (EEG) spectral power and emotional responses during affective sound clip listening are important parameters. Hemispheric asymmetry in prefrontal activation have been proposed in two decades ago, as measured by power value, is related to reactivity to affectively pleasure audio stimuli. In this study, we designed an emotional audio stimulus experiment in order to verify frontal EEG asymmetry by analyzing Event-related Spectral Perturbation (ERSP) results. Thirty healthy college male students volunteered the stimulus experiment with the standard IADS(International Affective Digital Sounds) clips. These affective sound clips are classified in three emotion states, high pleasure-high arousal (happy), middle pleasure-low arousal (neutral) and low pleasure-high arousal (fear). The analysis of the data was performed in both theta (4-8Hz) and alpha (8-13Hz) bands. ERSP maps in the alpha band revealed that there are the stronger power responses of high pleasure (happy) in the right frontal lobe, while the stronger power responses of middle-low pleasure (neutral and fear) in the left frontal lobe. Moreover, ERSP maps in the theta band revealed that there are the stronger power responses of high arousal (fear and happy) in the left pre-frontal lobe, while the stronger responses of low arousal (neutral) in the right pre-frontal lobe. However, the high pleasure emotions (happy) can elicit greater relative right EEG activity, while the low and middle pleasure emotions (fear and neutral) can elicit the greater relative left EEG activity. Additionally, the most differences of theta band have been found out in the medial frontal lobe, which is proved as the frontal midline theta. And there are the strongest responses of happy sounds in the alpha band around the whole frontal regions. These results are well suited for emotion recognition, and provide the evidences that theta and alpha powers may have the more important role in the emotion processing than previously believed.

• Annals of Clinical Neurophysiology
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• v.22 no.2
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• pp.82-91
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• 2020

Electroencephalography (EEG) produces time-series data of neural oscillations in the brain, and is one of the most commonly used methods for investigating both normal brain functions and brain disorders. Quantitative EEG analysis enables identification of frequencies and brain activity that are activated or impaired. With studies on the structural and functional networks of the brain, the concept of the brain as a complex network has been fundamental to understand normal brain functions and the pathophysiology of various neurological disorders. Functional connectivity is a measure of neural synchrony in the brain network that refers to the statistical interdependency between neural oscillations over time. In this review, we first discuss the basic methods of EEG analysis, including preprocessing, spectral analysis, and functional-connectivity and graph-theory measures. We then review previous EEG studies of brain network characterization in several neurological disorders, including epilepsy, Alzheimer's disease, dementia with Lewy bodies, and idiopathic rapid eye movement sleep behavior disorder. Identifying the EEG-based network characteristics might improve the understanding of disease processes and aid the development of novel therapeutic approaches for various neurological disorders.

• Journal of the Korean Society of Safety
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• v.23 no.3
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• pp.65-70
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• 2008

Electroencephalogram(EEG) would be the most objective psychophysiological research technique on human errors though few research has been taken yet. This study aimed to get characteristics of human error while committing simple Odd-Ball tasks by utilizing the power spectrum technique of EEG data. Each experiment was composed of 3 tasks with different rules, and three young undergraduate students participated in this study as paid subjects. The result showed that subject and the interaction of subject and task factors were statistically significant on variation of power of $\alpha$ and $\beta$ bands which implied there would exist groups with homogeneity in their response. And though the variation of band powers due to task factors were not so great as to get statistical significance, it implied that the task requiring decoding process would be more strange to human beings than the task merely requiring psychological recall process.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2010.05a
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• pp.37-41
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• 2010

The previous investigations of electroencephalogram (EEG) activity in the memory retrieval tasks demonstrated that event-related potentials (ERP) during recollection showed different durations and the peak levels from those without recollection. However, it has been unknown that recollection in memory retrieval also modulates high-frequency brain rhythms as well as establishes large-scale synchronization across different cortical areas. In this study, we examined the spectral components of the EEG signals, especially the gamma bands (20-80Hz), measured during the memory retrieval tasks. Specifically, we focused on two major spectral components: first, we evaluated the temporal patterns of the power spectral density before and after the onset of the memory retrieval task; second, we estimated phase synchrony between all possible pairs of EEG channels to evaluate large-scale synchronization. Fourteen healthy subjects performed the memory retrieval task in the virtual reality environment where they selected whether or not t he present item was seen in the previous training period. When the subjects viewed the unseen items, the middle gamma power (40-60Hz) appeared to increase 200-500ms after stimulus onset while the low gamma power (20Hz) was suppressed all the way through the post-stimulus period 150ms after onset. The degree of phase synchronization in this low gamma level, however, increased when the subjects fetched the item from memory. This suggests that phase synchrony analysis might reveal different aspects of the memory retrieval process than the gamma power, providing additional information to the inference on the brain dynamics during memory retrieval.

• Journal of Magnetics
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• v.17 no.2
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• pp.133-137
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• 2012

We investigated the effects of pulsed magnetic fields (PMF) stimulus on electroencephalogram (EEG) alpha activity and heart rate variability (HRV) from electrocardiogram (ECG) measurements with various stimulus durations at acupoint PC9. The alpha activity in the EEG and the ratio of low frequency power and high frequency power (LHR) in the HRV, a reflection of sympathovagal activity, were increased and decreased, respectively, after PMF stimulus of 3 min. Our spectral analysis quantitatively proved that the changes in the EEG alpha activity were consistent with an autonomic function in the ECG. These findings suggest that appropriate PMF stimulus results in the same effect as that of acupuncture applied to the acupoint PC9, which is closely related to the parasympathetic activity of the autonomic nervous system.

• Annals of Clinical Neurophysiology
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• v.3 no.1
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• pp.26-30
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• 2001

Purpose : Eyeball movement is one of the main artifacts in EEG. A new approach to the removal of these artifacts is presented using independent component analysis(ICA). This technique is a signal-processing algorithm to separate independent sources from unknown mixed signals. This study was performed to show that ICA is a useful method for the separation of EEG components with little data deformity. Methods : 12 sets of 10 sec digital EEG data including eye opening and closure were obtained using international 10~20 system scalp electrodes. ICA with 18 tracings of double banana bipolar montage was performed. Among obtained 18 independent components, two components, which were thought to be eyeball movements were removed. Other 16 components were reconstructed into original bipolar montage. Power spectral analysis of EEGs before and after ICA was done and compared statistically. Total 12 pairs of data were compared by visual inspection and relative power comparison. Results : Waveforms of each pair looked alike by visual inspection. Means of relative power before and after ICA were 29.16% vs. 28.27%, 12.12% vs. 12.41%, 10.55% vs. 10.52%, and 19.33% vs. 18. 33% for alpha, beta, theta, and delta, respectively. These values were statistically same before and after ICA. Conclusions : We found little data deformity after ICA and it was possible to isolate eyeball movements in EEG recordings. Many other components of EEG could be selectively separated using ICA.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.750-755
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• 2007

The linear SEF (Spectral Edge Frequency) parameter and spectrum analysis method can not reflect the non-linear of EEG. This method can not contribute to acquire real time analysis and obtain a high confidence in the clinic due to low discrimination. To solve the problems, the development of a new index is carried out using the bispectrum analyzing the EEG including the non-linear characteristic. At the bispectrum analysis of the 2 dimension, the most significant's power spectrum density peaks appeared much at the specific area in awake and anesthesia state. Because many peaks are showed at the specific area in the frequency coordinate, these points are used to create the new index. Range of the index is 0-100. At the anesthesia, the index is 20-50 and at the awake, the index is 90-60. New index can discriminate the awake and anesthesia state.