• 제목/요약/키워드: Portable EEG

검색결과 28건 처리시간 0.032초

Measuring the Degree of Content Immersion in a Non-experimental Environment Using a Portable EEG Device

  • Keum, Nam-Ho;Lee, Taek;Lee, Jung-Been;In, Hoh Peter
    • Journal of Information Processing Systems
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    • 제14권4호
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    • pp.1049-1061
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    • 2018
  • As mobile devices such as smartphones and tablet PCs become more popular, users are becoming accustomed to consuming a massive amount of multimedia content every day without time or space limitations. From the industry, the need for user satisfaction investigation has consequently emerged. Conventional methods to investigate user satisfaction usually employ user feedback surveys or interviews, which are considered manual, subjective, and inefficient. Therefore, the authors focus on a more objective method of investigating users' brainwaves to measure how much they enjoy their content. Particularly for multimedia content, it is natural that users will be immersed in the played content if they are satisfied with it. In this paper, the authors propose a method of using a portable and dry electroencephalogram (EEG) sensor device to overcome the limitations of the existing conventional methods and to further advance existing EEG-based studies. The proposed method uses a portable EEG sensor device that has a small, dry (i.e., not wet or adhesive), and simple sensor using a single channel, because the authors assume mobile device environments where users consider the features of portability and usability to be important. This paper presents how to measure attention, gauge and compute a score of user's content immersion level after addressing some technical details related to adopting the portable EEG sensor device. Lastly, via an experiment, the authors verified a meaningful correlation between the computed scores and the actual user satisfaction scores.

A Portable Wireless EEG System for Neurofeedback: Design and Implementation

  • Chen, Hai-Feng;Ye, Dong-Hee;Kang, Young-Ho;Lee, Jung-Tae
    • 대한의용생체공학회:의공학회지
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    • 제28권4호
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    • pp.461-470
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    • 2007
  • Human can learn how to shape their brain electrical activity in a desired direction through continuous feedback of the electroencephalogram (EEG), and this technique is known as Neurofeedback (or EEG biofeedback), which has been used since the late 1960s in clinical applications. In this study, a portable wireless EEG (named wEEG) has been designed and implemented, which consists of a mobile station (a wireless two-channel EEG acquisition device) and a base station (a bridge between mobile station and computer). Moreover, a SensoriMotor Rhythm (SMR) training system was also implemented with the wEEG for enhancing attention with virtual environment. Experiment results based on 16 volunteers' (8 females and 8 males, average age is $27{\pm}4$) were reported in this paper. The results show that the SMR ratio of 87.5% subjects increased about 0.7% in training status than that in the stable status. With the proposed system, many training protocol scan be designed easily and can be done at home in our daily life conveniently. Additionally, the proposed system will be useful for disabled and aged people.

포터블 수면유도 뉴로피드백 시스템 구현을 위한 수면뇌파 상태 분류기 성능 평가 (Performance evaluation of sleep stage classifier for the sleep-inducing portable neurofeedback system)

  • 이택
    • 한국융합학회논문지
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    • 제9권11호
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    • pp.83-90
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    • 2018
  • 최근 많은 사람들이 불면증으로 인한 노동력저하, 인지기능저하, 정신질환 증가 등의 불편을 겪고 있다. 이에 대한 해결책은 인지치료나 약물치료가 거의 전부인 수준이나 부작용과 의존성 문제로 인해 장기적으로는 권장되지 않는 방법이다. 따라서 본 논문에서는 수면 유도에 도움이 되는 포터블 뇌파 측정기 기반 뉴로피드백 시스템을 제안한다. 그리고 시스템을 구현하는 데 가장 핵심적인 기능인 뇌파 상태 분류기를 설계하고 평가하며 성능에 영향을 미칠 수 있는 여러 요인들에 대해 최적화된 분류기 모델링 방법을 제시한다. 제안한 분류기를 이용할 시 포터블 뇌파 측정기에서 각성과 수면 단계를 97.9% 정확하게 구분할 수 있었다.

웨이블릿 패킷 분해를 이용한 EEG 신호압축 (EEG Data Compression Using the Feature of Wavelet Packet Coefficients)

  • 조현숙;이형;황선태
    • Journal of Information Technology Applications and Management
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    • 제10권4호
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    • pp.159-168
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    • 2003
  • This paper is concerned with the compression of EEG signals using wavelet-packet based techniques. EEG data compression is desirable for a number of reasons. Primarily it decreases for transmission time, archival storage space, and in portable systems, it decreases memory requirements or increases channels and bandwidth. Upon wavelet decomposition, inherent redundancies in the signal can be removed through thresholding to achieve data compression. We proposed the energy cumulative function for deciding of the threshold value and it works very innovative of EEG data.

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포터블 EEG를 활용한 콘텐츠 몰입도 평가 (Measurement of degree of contents immersion with using the portable EEG device)

  • 금남호;이택;이정빈;인호
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2015년도 추계학술발표대회
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    • pp.1681-1684
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    • 2015
  • 최근 소형 모바일 디바이스가 발달함에 따라 시간적, 공간적 제약이 없이 대량의 콘텐츠가 소비되고 있는 환경에서 콘텐츠 소비 만족도 및 몰입도를 측정하기 위해 사용자 피드백을 설문 조사하는 기존 방식은 비효율적이다. 왜냐하면 수작업에 의존하고 객관성이 결여된 데이터가 수집될 가능성이 있기 때문이다. 따라서 최근 연구에서는 EEG를 활용한 방법이 하나의 대안으로 제시되고 있다. 본 논문에서는 기존 설문조사 방식의 한계점을 보완하고 기존 EEG방식의 단점을 개선하기 위한 포터블 EEG를 활용하는 방법을 제안하였다. 소형 및 간편함을 확보하기 위하여 배터리 환경에 비 접착식 단일전극을 이용하여 EEG를 측정하고 주파수 분석을 통하여 집중력과 관련된 파형을 분리, 콘텐츠 몰입도를 점수화 하였다. 마지막으로 실험을 통해 앞서 산출한 점수와 콘텐츠의 흥미도가 비례관계에 있음을 증명하였다.

뇌-컴퓨터-인터페이스를 이용한 암환자들의 전전두엽 뇌파 분석 (Patterns Analysis of Prefrontal Brain Waves of Cancer Patients using Brain-Computer-Interface)

  • 한영수;채명신;박병운;박종기
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제35권3호
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    • pp.169-178
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    • 2008
  • 암환자들은 암의 진행과 항암화학요법 등의 치료로 인해 심신의 불안정과 항상성의 저하로 큰 고통을 겪고 있다. 간편하면서 인체에 아무 해를 주지 않는 뇌파를 기반으로 하는 뇌-컴퓨터-인터페이스(BCI) 기술로서 암 환자의 상태를 모니터링하여 적절한 처치를 취할 수 있다는 것은 매우 중요한 일이다. 암환자들의 전전두엽에 헤드밴드 형태의 건성전극단자를 부착하고, 컴퓨터와 연결된 휴대용 뇌파측정 장치로 전전두엽 뇌파(Fp1, Fp2)를 측정하였다. 컴퓨터를 통하여 파장대 별로 얻어진 뇌파를 상호 연관성에 따라 뇌지수로 구분한 후 통계 처리하여 유의성을 검증하였다. 암환자군과 정상대조군을 비교한 결과 암환자군에 비하여 정상대조군이 기초율동지수, 주의지수, 정서지수, 항스트레지수와 좌우뇌균형지수에서 유의하게 높은 차이를 나타냈다. 따라서 뇌파 측정이 환자의 상태를 모니터링하는 중요한 도구로서의 가능성을 보였다.

최소 제곱 가속 기반의 적응 디지털 필터를 이용한 두피 뇌전도에서의 심전도 잡음 추정 및 제거 (A Method for Estimation and Elimination of EGG Artifacts from Scalp EEG Using the Least Squares Acceleration Based Adaptive Digital Filter)

  • 조성필;송미혜;박호동;이경중
    • 전기학회논문지
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    • 제56권7호
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    • pp.1331-1338
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    • 2007
  • A new method for detecting and eliminating the Electrocardiogram(ECG) artifact from the scalp Electroencephalogram(EEG) is proposed. Based on the single channel EEG, the proposed method consists of 4 procedures: emphasizing the R-wave of ECG artifact from EEG using the least squares acceleration(LSA) filter, detecting the R-wave from the LSA filtered EEG using the phase space method and R-R interval, generating the delayed impulse synchronized to the R-wave and elimination of the ECG artifacts based on the adaptive digital filter using the impulse and raw EEG. The performance of the proposed method was evaluated in the two separating parts of R-wave detection and, ECG estimation and elimination from EEG. In the R-wave detection, the proposed method showed the mean error rate of 6.285(%). In the ECG estimation and elimination using simulated and/or real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, in which independent component analysis and ensemble average method are used. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifact from single channel EEG and simple for ambulatory/portable EEG monitoring system.

휴대용 수면 패턴 모니터링을 위한 복합 fNIRS-EEG 시스템 개발 (Development of a Hybrid fNIRS-EEG System for a Portable Sleep Pattern Monitoring Device)

  • 김경한;우성우;하성훈;박금룡;사커 엠디 샤힌;박배정;김창세
    • 대한의용생체공학회:의공학회지
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    • 제44권6호
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    • pp.392-403
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    • 2023
  • This study presents a new hybrid fNIRS-EEG system to meet the demand for a lightweight and low-cost sleep pattern monitoring device. For multiple-channel configuration, a six-channel electroencephalogram (EEG) and a functional near-infrared spectroscopy (fNIRS) system with eight photodiodes (PD) and four dual-wavelength LEDs are designed. To enhance the convenience of signal measurement, the device is miniaturized into a patch-like form, enabling simultaneous measurement on the forehead. Due to its fully integrated functionality, the developed system is advantageous for performing sleep stage classification with high-temporal and spatial resolution data. This can be realized by utilizing a two-dimensional (2D) brain activation map based on the concentration changes in oxyhemoglobin and deoxyhemoglobin during sleep stage transitions. For the system verification, the phantom model with known optical properties was tested at first, and then the sleep experiment for a human subject was conducted. The experimental results show that the developed system qualifies as a portable hybrid fNIRS-EEG sleep pattern monitoring device.

단일 채널 두피 뇌전도에서의 심전도 잡음 추정 및 제거 (Estimation and Elimination of ECG Artifacts from Single Channel Scalp EEG)

  • 조성필;송미혜;박호동;이경중;박영철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 제38회 하계학술대회
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    • pp.1910-1911
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    • 2007
  • A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. In conclusion, we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

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DSP보드를 이용한 뇌파의 외부잡음 제거용 적응필터 및 피드백 출력제어 알고리듬 (The Adaptive Filter for EEG Artifact Cancellation and the Feedback Output Control Algorithm on the DSP Board)

  • 안보섭;박정제;이경일;박일용;조진호;김명남
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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    • pp.548-551
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    • 2003
  • The adaptive filter is proposed for removing EOG from measured EEG on the frontal lobe. The proposed adaptive filter has been implemented and the feedback output control algorithm has been employed to control the alpha wave ratio on the basis of TMS320C31 DSP board with the on-line and real time performance. The feedback algorithm controls the input voltage of stimulating devices on the portable bio-feedback system. The EEG data are acquired at the $F_{p1}$ and $F_{p2}$ localization and are processed by the proposed adaptive filter. We demonstrated that the proposed adaptive filter could effectively remove EOG from the measured EEG on the frontal lobe and the feedback algorithm is proper to control the output voltage of DSP board using the ratio of the alpha wave.

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