• Journal of Dental Anesthesia and Pain Medicine
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• v.17 no.4
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• pp.241-251
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• 2017

Devices that monitor the depth of hypnosis based on the electroencephalogram (EEG) have long been commercialized, and clinicians use these to titrate the dosage of hypnotic agents. However, these have not yet been accepted as standard monitoring devices for anesthesiology. The primary reason is that the use of these monitoring devices does not completely prevent awareness during surgery, and the development of these devices has not taken into account the neurophysiological mechanisms of hypnotic agents, thus making it possible to show different levels of unconsciousness in the same brain status. An alternative is to monitor EEGs that are not signal processed with numerical values presented by these monitoring devices. Several studies have reported that power spectral analysis alone can distinguish the effects of different hypnotic agents on consciousness changes. This paper introduces the basic concept of power spectral analysis and introduces the EEG characteristics of various hypnotic agents that are used in sedation.

• Korean Journal of Acupuncture
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• v.29 no.3
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• pp.467-475
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• 2012

Objectives : The aim of this study was to examine the effects of Acupuncture at the GV20 and GV22 on normal human beings using power spectrum analysis. Methods : Electroencephalogram(EEG) power spectrum exhibits site-specific and state-related differences in various frequency bands. 8 channels Background Electroencephalogram (EEG) was carried out in 30 subjects(24 females and 4 males). Results : In ${\delta}$(theta) band, the power values decreased significantly at the 8-channel average value(p=0.03) and especially at T3(p=0.02), T4(p=0.001) and P3(p=0.03). In ${\alpha}$(alpha) band, the power values have no significant changes. In ${\beta}$(beta)band, the power values increased significantly at the 8-channel average value (p=0.02) and especially at T4(p=0.003), P3 (p= 0.03) and P4(0.02). In ${\beta}/{\delta}$(beta/theta) ratio, the value increased significantly at the 8-channel average value(p=0.002) and especially at Fp2(p=0.05), F4(p=0.007), T3(0.012), T4(0.005), P3 (0.007) and P4(0.03) Conclusions : Through this data, we conclude that acupuncture at the GV20 and GV22 on normal human beings could have possibility to awake the cerebral cortex by the functional mechanism.

• The Journal of Korean Physical Therapy
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• v.29 no.5
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• pp.227-233
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• 2017

Purpose: The aim of this study was to determine if Pilates gymball exercise can change the electroencephalogram and cognitive function of mentally disabled people. Methods: Twenty-one mentally disabled people were enrolled in this study. They were assigned randomly to one of two groups: Pilates gymball exercise group (PGEG, n=11), and control group (CG, n=10). The subjects in the PGEG group performed the exercises for 50 minutes a day, three days per week for 6 weeks. The PGEG program consisted of warm up (10 minutes), main workout (30 minutes), and cool down (10 minutes). The main workout consisted of 10 exercise programs. The electroencephalogram (EEG) of Fp1, Fp2, F3, F4, C3, C4, O1, and O2 were measured using an PolyG-I system. The cognitive function was evaluated using a mini-mental state examination (MMSE). The measurements were performed before exercise, and 6 weeks after exercise. Covariance analysis (ANCOVA) was performed to determine the difference between the two groups Results: A significant difference in Fp1, Fp2, and F3 on the relative alpha power was observed between the PGEG and CG groups (p<0.05). A significant difference in Fp1 on the relative beta power was observed between the PGEG and CG groups (p<0.05). No significant difference in the MMSE score was observed between the PGEG and CG groups. Conclusion: Pilates gymball exercise did positively change the EEG in the frontal lobe. On the other hand, the effect related to cognitive was limited. Pilates gymball exercise appears to be more effective in facilitating brain stimulation related to cognition.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.38-46
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• 2024

In general, EEG signal analysis has been the subject of several studies due to its ability to provide an objective mode of recording brain stimulation, which is widely used in brain-computer interface research with applications in medical diagnosis and rehabilitation engineering. In this study, we developed EEG reception hardware to measure electroencephalograms and implemented a processing system, classifying it into server and data processing. It was conducted as an intermediate-stage research on the implementation of a brain-computer interface using electroencephalograms, and was implemented in the form of predicting the user's arm movements according to measured electroencephalogram data. Electroencephalogram measurements were performed using input from four electrodes through an analog-to-digital converter. After sending this to the server through a communication process, we designed and implemented a system flow in which the server classifies the electroencephalogram input using a convolutional neural network model and displays the results on the user terminal.

• Physical Therapy Rehabilitation Science
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• v.1 no.1
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• pp.13-16
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• 2012

Objective: Electroencephalogram (EGG)-feedback is a training procedure aimed at altering brain activity, and is used as a treatment for disorders like attention. The purpose of this study was to determine the effects of external focus of attention by EGG-feedback on balance in young adults. Design: Cross-sectional study. Methods: Subject were students in Sahmyook University. Fifty young adults in their twenties and thirties. Subjects were performed both with and without external focus of attention by EEG-feedback on the posture of standing and tandem standing. Participants were educated effort to maintain static posture when they were under internal focus of attention. Good Balance System was used for measurement of postural consistency upon the following force platforms. Results: Body sway decreased significantly both normal standing and tandem standing with external focus of attention by EEG-feedback (p<0.05). Conclusions: The results demonstrate that the benefits of an external attentional focus are generalizable to young adults. The external focus of attention outperformed the internal focus of attention on the postural balance (p<0.05). It is showed that external focus of attention significant effects on balance by revoked automatic postural control of movement. Furthermore balance might be improved by training with an external focus. Further study is required to develop for training as a method of preventing fall in elderly peoples.

• 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 Internet Computing and Services
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• v.10 no.5
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• pp.127-133
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• 2009

This paper presents an approach to classify normal and epilepsy from electroencephalogram(EEG) using a neural network with weighted fuzzy membership functions(NEWFM). To extract input features used in NEWFM, wavelet transform is used in the first step. In the second step, the frequency distribution of signal and the amount of changes in frequency distribution are used for extracting twenty-four numbers of input features from coefficients and approximations produced by wavelet transform in the previous step. NEWFM classifies normal and epilepsy using twenty four numbers of input features, and then the accuracy rate is 98%.

• KIEAE Journal
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• v.11 no.3
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• pp.49-56
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• 2011

The effect of soundscape has been analyzed by questionnaire results. Nowadays, EEG is used to identify the human reponses due to exterior stimuli such as soundscape sound sources. So, it is very meaningful to know the EEG response to soundscape sound sources. In the present study, the sound sources of soundscape were heard to subjects in order to find out the relationship between questionnaire results and electroencephalogram results through lab test. And stimulated part of brain for evaluating words were sought in this experiment too. The results of the study are as follows : the sound source of bird+music causes more ${\alpha}$-wave rise than other sound sources and the ${\alpha}$-wave stimulated region of brain is occipitallobe. In case of ${\beta}$-wave, the left part of brain is excited. ${\delta}$-wave is on frontallobe and ${\Theta}$-wave is on right part of brain. The evaluating words for soundscape can be categorized into four groups. These results could be used for basic materials of soundscape effects analysis.

• Journal of Biomedical Engineering Research
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• v.22 no.1
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• pp.81-90
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• 2001

본 연구에서는 디지털 영상 뇌파계(digital video electroencephalogram, Digital VEEG)에서 비디오 영상과 뇌전도 파형의 동기화된 편집 시스템을 구성한다. 이 시스템은 기존 아날로그 영상 뇌파계(analog video electroencephalogram)의 동기화 문제와 디지털 영상 시스템에서의 영상편집 문제를 해결하기 위하여 MPEG-I(이하 MPEG) 고압축 기술을 이용한 MPEG 인코딩 보드(encoding board)와 MPEG 편집 엔진(editing engine)을 각각 사용하였다. 시스템은 디지털 영상뇌파계모듈과 디지털 편집 모듈로 구성되며, 뇌전도모듈에서는 환자에게 연결된 전극을 통해 들어온 뇌파를 생체신호증폭기를 이용하여 증폭한 후 AD 보드(analog to digital board)를 이용 디지털화한다. 디지털 카메라로 촬영된 환자영상의 아날로그 영상신호(NTSC 신호)는 MPEG 인코딩 보드를 이용하여 고압축 디지털화한다. 이후 디지털화된 뇌전도신호와 MPEG 형식의 영상을 시간 동기화하여 두 개의 모니터에 각각보여준다. 편집 모듈에서는 영상신호와 뇌파신호를 어느 부분이든 간단한 조작으로 오려 붙이기(cut and paste) 기능을 이용할 수 있다. 본 시스템은 사용된 데이터 모두 디지털 기술을 이용하여 영상과 뇌파신호의 정확한 동기화 및 각각의 데이터의 오려 붙이기 기능을 가능케 하였으며, 이는 환자의 데이터를 관리 및 보관하는데 있어, 임상의에게 의미 있는 자료만을 모아서 효율적으로 관리할 수 있게 해준다. 이와 같은 장점을 갖는 디지 영상뇌파계 편집시스템을 구현하였다.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.115-121
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• 2022

In this paper, we propose a music classification system according to user emotions using Electroencephalogram (EEG) features that appear when listening to music. In the proposed system, the relationship between the emotional EEG features extracted from EEG signals and the auditory features extracted from music signals is learned through a deep regression neural network. The proposed system based on the regression model automatically generates EEG features mapped to the auditory characteristics of the input music, and automatically classifies music by applying these features to an attention-based deep neural network. The experimental results suggest the music classification accuracy of the proposed automatic music classification framework.