• 제목/요약/키워드: Spike signal

검색결과 43건 처리시간 0.026초

근피로도 측정을 위한 중간 주파수와 Spike 파라미터의 신뢰도 비교 및 향상된 Spike 검출 알고리듬에 관한 연구 (A Study on the Reliability Comparison of Median Frequency and Spike Parameter and the Improved Spike Detection Algorithm for the Muscle Fatigue Measurement)

  • 이성주;홍기룡;이태우;이상훈;김성환
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권5호
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    • pp.380-388
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    • 2004
  • This study proposed an improved spike detection algorithm which automatically detects suitable spike threshold on the amplitude of surface electromyography(SEMG) signal during isometric contraction. The EMG data from the low back muscles was obtained in six channels and the proposed signal processing algorithm is compared with the median frequency and Gabriel's spike parameter. As a result, the reliability of spike parameter was inferior to the median frequency. This fact indicates that a spike parameter is inadequate for analysis of multi-channel EMG signal. Because of uncertainty of fixed spike threshold, the improved spike detection algorithm was proposed. It automatically detects suitable spike threshold depending on the amplitude of the EMG signal, and the proposed algorithm was able to detect optimal threshold based on mCFAR(modified Constant False Alarm Rate) in the every EMG channel. In conclusion, from the reliability points of view, neither median frequency nor existing spike detection algorithm was superior to the proposed method.

일정한 자의 수축 시 표면 근전도 신호에 대한 Spike 변수 해석 (Spike Variable Analysis of Surface EMG Signal During Constant Voluntary Contraction)

  • 양희원;정의곤;이진
    • 전기학회논문지
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    • 제56권4호
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    • pp.809-816
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    • 2007
  • This paper presents an analysis of the SEMG signal quantitatively and automatically using spike variables : MSF, MSA, MSS, and MSD. The SEMG signals were recorded in three muscle parts, first dorsal interosseus, biceps brachii and abductor policis brevis, from 14 normal subjects. Emphasis was placed on the following 3 points in the experiments. 1) Suggest proper window length to estimate the spike variables 2) Investigate variation of the spike variables to varying %MVC. 3) Investigate variation of the spike variables to the sustained contraction for 30 minutes. Quantitative results were showed and examined in point of practical clinical application.

다채널 실시간 신경신호 기록 및 신경계 분석을 위한 시스템의 개발 (Development of Multichannel Real Time Data Acquisition and Signal Processing System for Nervous System Analysis)

  • 김상돌;김경환;김성준
    • 대한의용생체공학회:의공학회지
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    • 제21권5호
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    • pp.469-475
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    • 2000
  • 신경신호의 계측은 신경계의 연구에 필수적인 도구로 최근 반도체미세전극기술 등 수십, 수백개의 채널로부터 신경신호를 기록할 수 있는 방법들이 발달함에 따라 많은 수의 뉴런으로부터 신경 신호를 측정하여 컴퓨터로 그 신호를 처리할 수 있는 시스템의 필요성은 더욱 커지고 있다. 본 연구에서는 최대 16채널의 신경신호를 실시간에 측정하여 기록하고, 저장된 신호로부터 활동전위를 검출하며, 단일 뉴런들로부터의 신호를 분류하여 spike train의 형태로 저장한 뒤 여러 뉴런들간의 상관관계를 분석하기 위한 spike train 해석이 가능한 시스템을 개발하였다. 이 시스템은 보통사양의 PC이외에는 단지 신호획득보드만을 포함하여 다채널미세전극으로부터 뉴런의 신호를 측정, 증폭하여 호스트PC로 전송하고 저장하며 이로부터 활동전위를 검출하여 단일뉴런으로부터의 spike train으로 분류할 수 있다. 또한 저장된 spike train들로부터 신경회로망을 이루는 여러뉴런 들간의 관계를 분석하여 기능들이 시스템에 포함되어있다. 개발된 시스템을 사용하여 개구리 감각 신경의 신호를 실시간에 동시기록하여 활동전위을 검출하고 특징추출방법과 principal component analysis를 이용하여 분류한 뒤 spike train 해석을 수행하였다.

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Improved Algorithm for Fully-automated Neural Spike Sorting based on Projection Pursuit and Gaussian Mixture Model

  • Kim, Kyung-Hwan
    • International Journal of Control, Automation, and Systems
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    • 제4권6호
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    • pp.705-713
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    • 2006
  • For the analysis of multiunit extracellular neural signals as multiple spike trains, neural spike sorting is essential. Existing algorithms for the spike sorting have been unsatisfactory when the signal-to-noise ratio(SNR) is low, especially for implementation of fully-automated systems. We present a novel method that shows satisfactory performance even under low SNR, and compare its performance with a recent method based on principal component analysis(PCA) and fuzzy c-means(FCM) clustering algorithm. Our system consists of a spike detector that shows high performance under low SNR, a feature extractor that utilizes projection pursuit based on negentropy maximization, and an unsupervised classifier based on Gaussian mixture model. It is shown that the proposed feature extractor gives better performance compared to the PCA, and the proposed combination of spike detector, feature extraction, and unsupervised classification yields much better performance than the PCA-FCM, in that the realization of fully-automated unsupervised spike sorting becomes more feasible.

Design of a CT Saturation Detection Technique with the Countermeasure for a Spike Signal

  • Kang, Yong-Cheol;Yun, Jae-Sung
    • KIEE International Transactions on Power Engineering
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    • 제3A권2호
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    • pp.85-92
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    • 2003
  • When a current transformer (CT) is saturated, the wave-shape of the secondary current is distorted and contains points of inflection, which correspond to the start or end of each saturation period. Discontinuity in the first-difference function of the current arises at points of inflection, where the second and third differences convert into pulses that can be used to detect saturation. This paper describes the design and evaluation of a CT saturation detection technique using the third-difference function and includes the countermeasure for a spike signal. Test results clearly demonstrate that the algorithm successfully detects the start and end of each saturation period irrespective of the remanent flux and magnetization inductance in the saturated region. This paper concludes by describing the results of hardware implementation of the algorithm using a DSP.

Illumination Control in Visible Light Communication Using Manchester Code with Sync-Mark Signal

  • Lee, Seong-Ho
    • 센서학회지
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    • 제29권3호
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    • pp.149-155
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    • 2020
  • In this study, we employed Manchester code for illumination control and flicker prevention of the light-emitting diode (LED) used in a visible light communication (VLC) system. In the VLC transmitter, the duty factor of the Manchester code was utilized for illumination control; in the VLC receiver, the spike signal from an RC-high pass filter was utilized to recover the transmitted signal whilst suppressing the 120-Hz noise arising from adjacent lighting lamps. Instead of the clock being transmitted in a separate channel, a syncmark signal was transmitted in front of each data byte and used as the reference time for transforming the Manchester code to non-return-to-zero (NRZ) data in the receiver. In experiments, the LED illumination was controlled in the range of approximately 12-84% of the constant wave (CW) light via changing of the duty factor from 10% to 90%. This scheme is useful for constructing indoor wireless sensor networks using LED light that is flicker-free and presents capability for illumination control.

Flicker Prevention and Noise Reduction Using Edge-Spike Modulation in Visible Light Communication

  • Lee, Seong-Ho
    • 센서학회지
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    • 제27권3호
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    • pp.143-149
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    • 2018
  • In this paper, we introduce an edge-spike modulation method for visible light communication (VLC). This method is effective in preventing LED flicker and 120 Hz noise interference in base-band VLC. In the VLC transmitter, edge-spikes are generated by passing the digital data through a simple RC-high pass filter (HPF). The LED modulation of the edge-spikes does not change the average power of the LED light; thus it prevents LED flicker. In the VLC receiver, the 120 Hz noise from other lighting lamps is easily eliminated by RC-HPF, while the edge-spike signal is detected normally. In our experiment, the message of an air-quality sensor was successfully transmitted using edge-spike modulation. This structure is useful in constructing, e.g., wireless gas monitoring sensor systems to warn and prevent harmful gas leakage accidents in buildings using LED light.

비선형매핑 기반 뇌-기계 인터페이스를 위한 신경신호 spike train 디코딩 방법 (Neuronal Spike Train Decoding Methods for the Brain-Machine Interface Using Nonlinear Mapping)

  • 김경환;김성신;김성준
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권7호
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    • pp.468-474
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    • 2005
  • Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.

Spike와 Turn 변수를 이용한 표면근전도 신호의 진폭 추정 (Surface EMG Amplitude Estimation by using Spike and Turn Variables)

  • 이진
    • 전기학회논문지
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    • 제67권1호
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    • pp.124-130
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    • 2018
  • The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is of high relevance not only in biomechanical studies but also more and more in clinical applications. This paper presents a new approach to estimate surface EMG amplitude by using the mean spike and mean turn amplitude(MSA and MTA) variables. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction and performance of the MSA and MTA variables applied to amplitude estimation of the EMG signals were investigated. To examine the performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that MSA and MTA amplitude estimations with first order whitening filter and 300[ms]-350[ms] moving average window length are optimal and show better performance(mean SNR improvement of 6%-15%) than the most frequently used variables(ARV and RMS).

학습 가능한 실시간 다단위 신경 신호의 분류에 관한 연구 (Classification of Multi-Unit Neural Action Potential by Template Learning)

  • 김상돌;김경환;김성준
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 추계학술대회
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    • pp.99-102
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    • 1997
  • A neural spike sorting technique has been developed that also has the capability of template learning. A system of software has been written that first obtains the templates by learning, and then performs the sorting of the spikes into single units. The spike sorting can be done in real time. The template learning consists of spike detection based on the discrete Haar transform (DHT), feature extraction by clustering of spike amplitude and duration, classification based on rms error, and fabrication of templates. The developed algorithms can be implemented into real time systems using digital signal processors.

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