• Clinical and Experimental Pediatrics
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• 제59권sup1호
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• pp.157-160
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• 2016

Coexistence of paroxysmal kinesigenic dyskinesia (PKD) with benign infantile convulsion (BIC) and centrotemporal spikes (CTS) is very rare. A 10-year-old girl presented with a 3-year history of frequent attacks of staggering while laughing and of suddenly collapsing while walking. Interictal electroencephalogram (EEG) revealed bilateral CTS, but no changes in EEG were observed during movement. The patient's medical history showed afebrile seizures 6 months after birth, while the family history showed that the patient's mother and relatives on the mother's side had similar dyskinesia. Genetic testing demonstrated that the patient had a heterozygous mutation, c.649_650insC, in the PRRT2 gene. To our knowledge, this constitutes only the second report of a patient with PKD, BIC, CTS, and a PRRT2 mutation.

• Fisheries and Aquatic Sciences
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• 제17권1호
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• pp.19-25
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• 2014

We investigated the effects of Ecklonia cava ethanol extract (ECE) on sleep architecture and sleep profiles. ECE was orally administered at a dose of 100, 250, or 500 mg/kg to C57BL/6N mice and its effects were measured by recording electroencephalogram (EEG) and electromyogram. Administration of ECE (250 and 500 mg/kg) significantly induced non-rapid eye movement sleep (NREMS) without affecting rapid eye movement sleep. The increase in NREMS by ECE (500 mg/kg) was significant (P < 0.05) during the first 2 h after administration. In addition, ECE had no effect on EEG power density (an indicator of sleep quality) in NREMS. These results suggest that ECE induces NREMS in a manner similar to physiological sleep.

• 융합신호처리학회논문지
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• 제13권3호
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• pp.136-141
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• 2012

운전 중 운전자의 졸음은 교통 사망사고를 일으키는 중요한 요인이며 음주운전보다도 더 위험할 수 도 있다. 이러한 이유로 운전자의 졸음을 판별하고 경고하는 시스템 개발이 최근에 매우 중요한 이슈로 떠올랐다. 그중에서도 졸음과 가장 밀접한 관련이 있는 생체 신호인 뇌파 (Electroencephalogram, EEG)와 안구전도 (Electrooculogram, EOG)를 분석하는 연구가 주류를 이루고 있다. 본 논문에서는 실험 프로토콜에 의거하여 측정된 뇌파를 주파수별로 분석하여 운전자의 상태별 뇌파 데이터베이스를 구축하고 선형예측(Linear Predictive coding, LPC) 계수를 특징벡터로 한 신경회로망 기반 운전자 졸음 감지 시스템을 제안한다. 실험결과로 졸음의 뇌파분석에서 알파파가 감소하며 세타파가 증가하는 추세를 보였으며, LPC 계수가 각성, 졸음 및 수면상태의 특징을 잘 반영하였다. 특히 제안한 시스템은 적은 샘플(250ms)을 가지고도 96.5%라는 높은 분류 결과를 얻어 짧은 순간에 일어날 수 있는 운전 시 돌발 상황을 실시간으로 검출 가능성을 확인하였다.

• 한국통신학회논문지
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• 제38C권7호
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• pp.623-629
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• 2013

본 논문에서는 뇌파 전송 프로토콜 설계하고 이를 검증할 테스트 플랫폼 제작 결과를 소개한다. 건식 전극에서 검출된 뇌파는 인접한 ADC(analog-to-digital converter)를 거쳐 디지털 신호로 변환되고, 각 센서 노드에서 디지털 신호로 변환된 뇌파는 $I^2C$(inter-integrated circuit) 프로토콜을 통해서 DSP(digital signal processor) 플랫폼으로 전송된다. DSP 플랫폼에서는 뇌파 전처리 알고리즘 수행 및 뇌 특성 벡터 추출 등의 기능을 수행한다. 본 연구에서는 각 채널당 10비트 또는 12비트 ADC를 사용하여 최대 16채널의 데이터를 전송하기 위하여 $I^2C$ 프로토콜을 적용하였다. 실험결과 4바이트 데이터 버스트전송을 수행하면 통신오버헤드가 2.16배로 측정이 되어 10 비트 또는 12 비트 1 ksps ADC를 16채널로 사용시 총 데이터전송율이 각각 345.6 kbps, 414.72 kbps 로 확인되었다. 따라서 400 kbps 고속전송모드 $I^2C$를 사용할 경우 ADC 비트에 따라서 슬레이브와 마스터의 채널비가 각각 16:1, $(8:1){\times}2$ 로 되어야 한다.

• 대한의용생체공학회:의공학회지
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• 제16권2호
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• pp.157-166
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• 1995

The Electroencephalogram (EEG) and evoked potential (EP) t;ave widely been used for study of brain functions. The EEG and EP signals acquired from multi-channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG). Since these artifact-affected EEG signals degrade EEG mapping, the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. In this paper a neural-network based classification is proposed to replace or to reduce human expert's efforts and time. From experiments, the neural-network based classification performs as good as human experts : variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• Annals of Clinical Neurophysiology
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• 제19권2호
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• pp.113-117
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• 2017

The performance of electroencephalogram (EEG) recordings is affected by electrode type, electronic parameters such as filtering, amplification, signal conversion, data storage; and environmental conditions. However, no single method has been identified for optimal EEG recording quality in all situations. Therefore, we aimed to provide general principles for EEG electrode selection as well as electronic noise reduction, and to present comprehensive information regarding the acquisition of satisfactory EEG signals. The standards provided in this document may be regarded as Korean guidelines for the clinical recording of EEG data. The equipment, types and nomenclature of electrodes, and the details for EEG recording are discussed.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 춘계학술대회
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• pp.75-78
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• 1994

To represent the overall potential distribution on the entire scalp it is necessary to interpolate between sampled EEG(electroencephalogram) values, we describe a method to interpolate between scalp recorded EEG data which obtained from electrodes irregularly disposed on the scalp, using polynomial interpolation. This method can analyze the variance of source temporally or spatially and present continuous distributed topographic mapping of the EEG records. In the result, we obtained the overall potentials distribution on the entire scalp from the EEG records of a patient which was known to epilepsy.

• 전기학회논문지
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• 제67권11호
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• pp.1506-1511
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• 2018

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, 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 degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that the proposed scheme achieved good performances for evaluation of human sensibility.

• 대한인간공학회지
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• 제23권4호
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• pp.57-66
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• 2004

EEG(Electroencephalogram) provides a possibility of communicating between a human and a computer, called BCI(brain computer interface). EEG evoked by a movement has been often used as a control command of a computer. This study is to predict human movements by EEG parameters showed significant consistency. Three undergraduate students were asked to move both hands and foots thirty times respectively. Each movement consisted of single and three consecutive movements. Their EEG signals were analyzed to obtained ERD(Event Related Desynchronization) and ERS(Event Related Synchronization). The results showed that ERD and ERS could be used as a significant classifier identifying either single movement or repetitive movement of human limbs. The number of repetition of movement could be used to various control commands of a computer.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 춘계학술발표대회
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• pp.847-850
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• 2016

뇌-컴퓨터 인터페이스(Brain-Computer Interface: BCI) 기술의 중요성 및 활용도가 증대됨으로써 EEG(electroencephalogram: EEG)기반의 사용자 인터페이스에 대한 개발 및 연구가 활발히 진행되고 있다. 그러나 뇌파 발생 훈련이 되어 있지 않은 사용자는 EEG 기반의 사용자 인터페이스를 사용하기가 어렵다. 따라서 본 논문에서는 향후 뇌파 훈련을 위한 시뮬레이터를 개발하고자, 그 전단계로 사용자에게서 공통적으로 정확도가 높게 측정되는 채널 및 특징점을 비교, 분석 하였다. 피험자 3명의 왼손 동작 상상과 오른손 동작 상상으로 발생된 EEG 생체신호로부터 ERD/ERS를 확인하고, 8개의 특징점을 추출하여 SVM 분류 알고리즘을 기반으로 정확도를 측정하였으며, ${\mu}$대역 채널 AF4, F4에서의 특징 MAV에서 가장 우수한 성능을 보였다.