• 제목/요약/키워드: EEG Signal

검색결과 360건 처리시간 0.026초

Interval estimate of physiological fluctuation of peak latency of ERP waveform based on a limited number of single sweep records

  • Nishida, Shigeto;Nakamura, Masatoshi;Suwazono, Shugo;Honda, Manabu;Nagamine, Takashi;Shibasaki, Hiroshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.1.1-5
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    • 1994
  • In the single sweep record of event-related potential (ERP), the peak latency of P300, which is one of the most prominent positive peaks in the ERP record, might fluctuate according to the recording conditions. The fluctuation of the peak latency (measurement fluctuation) is the summation of the fluctuation caused by physiological factor (physiological fluctuation) and one by noise of background EEG (noise fluctuation). We propsed a method for estimating the interval of the physiological fluctuation based on a limited number of single sweep records. The noise fluctuation was estimated by using the relationship between the signal-to-noise (SN) ratio and the noise fluctuation based on the P300 model and the background EEG model. The interval estimate of the physiological fluctuation were obtained by subtracting the interval estimate of the noise fluctuation from that of the measurement fluctuation. The proposed method was tested by using simulation data of ERP and applied to actual ERP and data of normal subjects, and gave satisfactory results.

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콤퓨터를 이용한 간질환자 뇌파의 극파 자동검출 방법에 관한 연구 (A Study on Computer-Assisted Automatic Spike Detection System in EEG Signal of Epileptic Patients)

  • 박광석;민병구;이충웅
    • 대한전자공학회논문지
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    • 제17권6호
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    • pp.28-32
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    • 1980
  • 병질우자의 뇌파에서 나타나는 비정상적인 극파(spike)를 삼각파형의 모델을 사용하여 자동검출하는 방법을 디지탈시스템으로 구성하였다. 이 방법은 극파가 일정한 시간폭과 큰 기울기와 정상에서 날카로운 특성을 갖는 파형이라는 성질을 이용한 것이다. 본 논문에서는 뇌파를 채집하여 신호처리한 다음 이러한 극파의 특성을 나타내는 모개변수들로부터 극파를 구별하여 판정해내는 프로그램을 구성하였다. 이러한 신호처리 과정과 검출과정을 모두 미니콤퓨터를 이용하여 구성했으며 마이크로프로세서에의 응용을 위한 기본단계라고 할 수 있다.

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Physiological Status Assessment of Locomotive Engineer During Train Operation

  • Song, Yong-Soo;Baek, Jong-Hyen;Hwang, Do-Sik;Lee, Jeong-Whan;Lee, Young-Jae;Park, Hee-Jung;Choi, Ju-Hyeon;Yang, Heui-Kyung
    • Journal of Electrical Engineering and Technology
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    • 제9권1호
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    • pp.324-333
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    • 2014
  • In this study, physiological status of locomotive engineers were measured through EEG, ECG, EDA, PPG and respiration signals from 6 subjects to evaluate their arousal status during train operating. Existence of tunnels and mechanical vibration of train using 3-axes acceleration sensors were recorded simultaneously and were correlated with operator's physiological status. As the result of the analyzed subjects' physiological signals, mean SCR was increased in the section where more body movement is required. The RR interval was decreased before and after train stop due to the higher level of mental tension. The intensity of beta wave of EEG was found to be higher before and after train stop and tunnel section due to the increased mental arousal and tension. Therefore, it is expected that the outcomes of the physiological signals explored in this study can be utilized as the quantitative assessment methods for the arousal status to be used for sleepiness prevention system for vehicles operators which can greatly contribute to public transportation system safety.

간질 분류를 위한 NEWFM 기반의 특징입력 및 퍼지규칙 추출 (Extracting Input Features and Fuzzy Rules for Classifying Epilepsy Based on NEWFM)

  • 이상홍;임준식
    • 인터넷정보학회논문지
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    • 제10권5호
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    • pp.127-133
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    • 2009
  • 본 논문은 가중 퍼지소속함수 기반 신경망(Neural Network with Weighted Fuzzy Membership Functions, NEWFM)을 이용하여 간질 증세를 가진 사람과 건강한 사람의 뇌파(electroencephalogram, EEG)로부터 정상 파형과 간질(epilepsy) 파형을 분류하는 방안을 제시하고 있다. NEWFM에서 사용할 특징입력을 추출하기 위해서 첫 번째 단계에서는 웨이블릿 변환(wavelet transform, WT)을 이용하였다. 두 번째 단계에서는 첫 번째 단계에서 생성한 웨이블릿 계수들을 주파수 분포와 주파수 변동량을 이용하여 24개의 특징입력을 추출하였다. NEWFM은 이들 24개의 특징입력을 이용하여 정상 파형과 간질 파형을 분류하였을 때 98%의 분류성능을 나타내었다.

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EOG를 사용한 가상현실 HMD용 키보드 구현 (Keyboard for Virtual Reality Head Mounted Display using Electro-oculogram)

  • 김병준;권기철;양용만;김남
    • 한국콘텐츠학회논문지
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    • 제18권1호
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    • pp.1-9
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    • 2018
  • 본 논문에서는 눈을 깜빡(eye-blink)일 때 발생하는 안전도(EOG, electro-oculogram) 신호를 이용하여 손을 사용하지 않는 가상현실 HMD(head mounted display)용 키보드 시스템을 제안하였다. 본 시스템은 디스플레이 소자, 자이로스코프센서, 중력센서, 뇌전도(EEG, electro-encephalogram) 센서 등으로 구성되며, 시스템의 제어 및 그래픽 처리 등을 위한 Unity3D 엔진으로 가상현실 HMD용 키보드 시스템을 구현하였다. 구현된 키보드의 방식은 한글의 경우 천지인 키보드 방식을 사용하였으며 영어, 숫자, 기호의 경우 $3{\times}4$ 방식을 사용하여 공간상의 문제를 해결하였다. 구현된 시스템을 통해 손을 사용하지 않고 목의 움직임과 안전도만으로 가상현실 HMD의 키보드 입력이 가능함을 확인하였다.

뇌파 분석을 통한 LED조명의 색온도와 조도가 집중도와 이완도에 미치는 영향 분석 (Analysis of the Effect on Attention and Relaxation Level by Correlated Color Temperature and Illuminance of LED Lighting using EEG Signal)

  • 신지예;천성용;이찬수
    • 조명전기설비학회논문지
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    • 제27권5호
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    • pp.9-17
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    • 2013
  • Preferred combinations of illuminance and color temperature of lighting depend on daily living activities. We investigated whether the illumination stimuli of LED lighting can enhance attention and relaxation level by controlling color temperature and illuminance level according to activities. Illuminations and color temperatures of LED flat panels are controlled in accordance with activities such as office work and resting. The attention and relaxation level under the task specific lightings are compared with those under normal lighting condition. Single channel EEG signals from the NeuroSky's Mindset are used to estimate attention and relaxation level of human subjects under different lighting conditions. Experiment results show that high color temperature with high illuminance of LED lightings (6600K, 800lx) shows improved attention level compared with conventional lighting conditions (4000K, 500lx).

SiMACS에서의 생체신호 수집 (Biological Signal Measurements in SiMACS)

  • 임지주;최용석;김동환;김은정;이현주;우응제;박승훈
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1994년도 춘계학술대회
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    • pp.53-56
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    • 1994
  • We have developed biological signal measurement modules and data acquisition and control card for a biological signal measurement, archiving, and communication system (SiMACS). Biological signals included in this system are ECG, EEG, EMG, invasive blood pressure, respiration, and temperature. Parameters of each module can be controlled by PC-base IDPU (intelligent data processing unit) through a data acquisition and control card. The data acquisition and control card can collect up to 16 channels of biological signals with sampling rate of $50\;{\sim}\;2,000Hz$ and 12-bit resolution. All measurement moduls and data acquisition functions are controlled by microcontroller which receives commands from PC. All data transfers among PC, microcontroller, and ADC are done through a shared RAM access by polling method for real rime operation.

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지그비 기반의 휴대형 심전도 모니터링 시스템 설계 (Design of Zigbee based Portable ECG monitoring system)

  • 홍주현;김남진;차은종;이태수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.51-53
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    • 2006
  • This paper proposes a portable ECG monitoring system, which integrates uptodate PDA and RF communication technology. The aim of the study is to acquire the subject's biomedical signal without any constraint. It has two types of transmission mode, which are total signal transmission mode and HR(heart rate)/SC(step count) transmission mode. In audition, wireless communication technology uses Zigbee Wireless PAN and can work in low-power mode, which is one of the advantages of ZiBbee communication technology. The developed system is composed of a transmitter and a receiver. The transmitter has three-axial acceleration sensor. ECG amplifier and Zigbee communication controller. In total signal transmission mode, it can send data 50 packets per second whose transmission speed corresponds to 300 ECG samples and 60 acceleration samples. In HR/SG transmission mode, it can calculate heart rate from EEG data with 216 samples per second and step count from acceleration data and send a packet every cardiac cycle. The receiver forwards the received data to PDA, where the data can be stored and displayed. Therefore, the developed device enables to continuous monitoring for Activities of Daily Living(ADL). Also, this method will reduce medical costs in the aged society.

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PPG 측정신호로부터의 심박 검출 성능 향상에 관한 연구 (A Study on the Performance Improvement of the HRV Detection from PPG Signals)

  • 최규식;최동혁;장윤승;양계탁
    • 한국항행학회논문지
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    • 제13권6호
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    • pp.926-932
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    • 2009
  • 건강에 관한 헬스케어기구 중에서 전신아마기의 보급이 급속도로 증가되고 있다. 현대인의 스트레스를 해소하기 위해 사용하는 이러한 전신안마기 사용시 PPG를 이용하여 HRV 신호를 측정하여 스트레스의 이완 정도를 판단하는 것이 중요하다. 그런데 이 경우 안마기에 의해서 피실험자가 움직이는 상태에서 측정이 이루어지므로 HRV의 측정신호에 동잡음이 개입된다. 본 논문에서는 이러한 복합신호에서 신호처리에 의해서 동잡음을 효과적으로 제거하여 원하는 HRV를 측정하여 분석하는 방법을 제시한다.

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Research on Stress Reduction Model Based on Transformer

  • Xu, Xin;Zhao, Yikun;Zhang, Ruhao;Xu, Tingting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권12호
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    • pp.3943-3959
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    • 2022
  • People are constantly exposed to stress and anxiety environment, which could contribute to a variety of psychological and physical health problems. Therefore, it is particularly important to identify psychological stress in time and to find a feasible and universal method of stress reduction. This research investigated the influence of different music, such as relaxation music and natural rhythm music, on stress relief based on Electroencephalogram signals. Mental arithmetic test was implemented to create a stressful environment. 23 participants performed the mental arithmetic test with and without music respectively, while their Electroencephalogram signal was recorded. The effect of music on stress relief was verified through stress test questionnaires, including Trait Anxiety Inventory (STAI-6) and Self-Stress Assessment. There was a significant change in the stress test questionnaire values with and without music according to paired t-test (p<0.01). Furthermore, a model based on Transformer for stress level classification from Electroencephalogram signal was proposed. Experimental results showed that the method of listening to relaxation music and natural rhythm music achieved the effect of reducing psychological stress and the proposed model yielded a promising accuracy in classifying the Electroencephalogram signal of mental stress.