• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.27-32
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• 2010

Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1190-1195
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• 2011

This paper presents a waist pressure evaluation method in human sensibility using a electroencephalogram(EEG) signal. For this objective, a size-controllable waist-belt is used. First of all, EEG signals for relaxed state are acquired. Then, the waist-belt of the subject is tightened about 90% of normal state. After a few minutes, the belt of the subject is released. Some necessary preprocessing is performed on the acquired signals, Linear Prediction (LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is used for indicating the state of body pressure. The results of the method showed 77.2% of coincidence with body pressure states. This may be compromising results for ssubject-independent sensibility evaluation using EEG signal.

• Biomedical Science Letters
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• v.18 no.4
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• pp.428-434
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• 2012

Epilepsy is a chronic neurological disease showing a symptom of repeated seizures without any other physical disorders. Among the diagnostic examination for epilepsy, the electroencephalogram (EEG) has been known as an important test. This study aimed to investigate the EEG with photic stimulation in the pediatric epilepsy patients. They underwent digital sleep and waking EEGs or waking EEGs with photic stimulation. Epilepsy type, seizure history, and season of occurring seizure were analyzed. Epilepsy patients showed more response during the period of photic-on and eye close at the frequency of 10~20 Hz during the EEG activation procedure. Photoparoxysmal response (PPR) was shown in 206 patients out of total 1,551 epilepsy patients. PPR was appeared more frequently during summer and winter seasons, and especially in the patients who had a history of seizure. During the PPR, EEG pattern showed spike (77.18%), theta (9.71%), and spike + theta (13.11%). On the other hand, beta and theta waves were not significantly changed by photic stimulation. However, alpha wave was decreased and delta wave was increased by photic stimulation (P<0.05). These changes may be due to temporarily altered electrophysiological function of the epileptic patient's brain by the photic stimulation. There was no difference in the EEG pattern between the left and right side in the brain. In conclusion, condition of photic-on with closed eyes and frequency of 10~20 Hz during the procedure of EEG activation could be appropriate for obtaining a definite photoparoxysmal response in the electroencephalogram of the pediatric epilepsy patients.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.251-256
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• 2008

Many researchers are studying about human Brain-Computer Interface(BCI) that it based on electroencephalogram(EEG) signals of multichannel. The researches of EEG signals are used for detection of a seizure or a epilepsy and as a lie detector. The researches about an interface between Brain and Computer have been studied robots control and game of using human brain as engineering recently. Especially, a field of brain studies used EEG signals is put emphasis on EEG artifacts elimination for correct signals. In this paper, we measure EEG signals as human emotions and divide it into five frequence parts. They are calculated related the percentage of selecting range to total range. the calculating values are compared standard values by Bayesian Network. lastly, we show the human face avatar as human Emotion.

• Journal of the Ergonomics Society of Korea
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• v.27 no.2
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• pp.9-14
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• 2008

Coherence can be used to evaluate the functional cortical connections between the motor cortex and muscle. This study is to find coherence between EEG (electroencephalogram) and EMG (electromyogram) evoked by movement of a hand. Seven healthy participants were asked to perform thirty repetitive movement of right hand for ten seconds with rest for ten seconds. Specific feature of EEG components has been extracted by ICA (independent component analysis) and coherence between EEG and EMG was analyzed from data measured EEG in five local areas around central part of head and EMG in flexer carpri radialis muscle during grabbing movement. Coherence between EEG and EMG was successfully obtained at 0.025 confidence limit during hand movement and showed significant difference between rest and movement at 13-18Hz.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.151-154
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• 2008

본 논문은 Bayesian Networks를 이용해서 EEG 신호를 분석해서 사람의 감정을 분석하는 방법을 제안하였다. 현제 연구자들은 Electroencephalogram(EEG) 신호를 기반으로 사람의 두뇌와 컴퓨터의 인터페이스에 관한 연구를 하고 있다. 기존에는 간질이나 발작 등을 의학 분야와 사람의 정서에 따라 뇌파분석을 하는 심리학의 영역에서 연구가 되어져 왔다. 최근에는 사람의 두뇌와 컴퓨터 간의 인터페이스를 통한 여러 가지 공학적인 접근이 이루어지고 있다. 본 논문에서는 사람의 감정에 따라 Brain-Computer Interface (BCI)를 통해서 EEG 신호를 분석하고 잡음을 제거해서 보다 정확한 신호를 추출한 다음 각각의 주파수 영역으로 분류를 하였다. 분류된 값들은 Bayesian Networks를 이용해서 피 실험자가 어떠한 감정을 나타내는지 확률 값으로 나타낸다. 확률 값에 의해서 피 실험자가 어떠한 감정인지를 인식하게 되는 것이다.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.179-188
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• 1996

A clinically oriented 32-channel electroencephalogram (EEG) and evoked potential (EP) mapping system has been developed EEG and EP signals acquired from 32-channel electrodes attached on the heroid surface are amplified by a pre-amplifier which is separated from main amplifier and is located near the patient to reduce signal attenuation and noise contamination between electrodes and the amplifier. The amplified signals are further amplified by a main amplifier where various filtering and gain contr61 are achieved An automatic artifact rejection scheme is employed using neural network-based EEG and artifact classifier, by which examination time is substantially reduce4 The continuously measured EEG sigrlals are used for spectral mapping, and auditory and visual evoked potentials measured in synchronous to the auditory and visual stimuli are used for temporal evoked potential mapping. A user-friendly graphical interface based on the Microsoft Window 3.1 is developed for the operation of the system. Statistical databases for comparisons of group and individual are included to support a statistically-based diagnosis.

• Annals of Clinical Neurophysiology
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• v.9 no.2
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• pp.69-74
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• 2007

Electroencephalogram (EEG) is a representative diagnostic tool in epilepsy. However, there are several points of debate on the role of EEG in diagnosis and management of epilepsy. We suggest that EEG has some limitations for differential diagnosis from nonepileptic episodic diseases, classification of epilepsy, prediction of recurrence, and evaluation of treatment response. Interictal EEG cannot diagnose or exclude epilepsy because interictal epileptic discharge (IED) is frequently absent in epilepsy and can appear in nonepileptic conditions. Although EEG is helpful in classification of epilepsy, focal spikes in generalized epilepsy and secondary bilateral synchrony in localization related epilepsy cause interrater disagreement. It is controversial whether EEG predicts recurrence after the first seizure in adults. The predictive value of EEG in antiepileptic drug (AED) withdrawal is not absolute. The prognosis after AED withdrawal depends on epilepsy syndrome. Many studies could not confirm the value of EEG in assessing the treatment response. After all, epilepsy is clinically diagnosed and assessed. Interictal EEG alone does not provide decisive information and routine follow-up of EEG is not recommended.

• Journal of Oriental Neuropsychiatry
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• v.32 no.4
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• pp.345-378
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• 2021

Objectives: The purpose of this study was to investigate the recent trends of clinical research on acupuncture using electroencephalogram (EEG) as the outcome measurement. Methods: Nine domestic and foreign databases were searched to collect related studies published up to November 3, 2021. The participants, intervention, outcomes, results of the included studies were extracted and analyzed. Results: A total of 18 studies were selected. Neurological diseases and mental disorders were included in most studies, and vascular dementia were most frequently investigated. Electroacupuncture and body acupuncture intervention were most frequently conducted in seven studies. The most commonly used outcomes using EEG was EEG abnormality. However, in most studies there was accurate description of the EEG measurement. Most studies showed significant difference in EEG outcomes after intervention. The quality of included studies was poor. Conclusions: EEG as diagnostic markers and outcome measurements is increasingly studied. Standardized EEG measurement and the consistent EEG finding for specific diseases are needed to perform the future rigorous studies on EEG as diagnostic and outcome tools.

• 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.