• 전자공학회논문지B
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• 제33B권6호
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• pp.164-175
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• 1996

In this thesis, to cope with severe intersymbol interference and nonlinear distotions of the digital magnetic recording channel a neural decision feedback equalizer (NDFE) and an adaptive neural equalizer (NE) are applied. The digital magnetic recording channels with various recording densities and different types of the nonlinear distortions are considered. The computer simulation shows that as the nonlinear distortion is increased, the neural equalizers (NdFE, NE) have advantages of approximately 2-4 dB in signal to noise ratio (SNR) over the onventional eualizers to reach sme bit error rate and, a sthe recording density is increased, 1~5 dB of SNR improvement are also gained. Especially the NdFE gives a superior performance over the other equalizers when there is a severe nonlinear distortion in the digital magnetic channel.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.195-196
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• 2007

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권1호
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• pp.129-140
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• 2017

In this paper, a $4{\times}32$-channel neural recording system capable of acquiring neural signals is introduced. Four 32-channel neural recording ICs, complex programmable logic devices (CPLDs), a micro controller unit (MCU) with USB interface, and a PC are used. Each neural recording IC, implemented in $0.18{\mu}m$ CMOS technology, includes 32 channels of analog front-ends (AFEs), a 32-to-1 analog multiplexer, and an analog-to-digital converter (ADC). The mid-band gain of the AFE is adjustable in four steps, and have a tunable bandwidth. The AFE has a mid-band gain of 54.5 dB to 65.7 dB and a bandwidth of 35.3 Hz to 5.8 kHz. The high-pass cutoff frequency of the AFE varies from 18.6 Hz to 154.7 Hz. The input-referred noise (IRN) of the AFE is $10.2{\mu}V_{rms}$. A high-resolution, low-power ADC with a high conversion speed achieves a signal-to-noise and distortion ratio (SNDR) of 50.63 dB and a spurious-free dynamic range (SFDR) of 63.88 dB, at a sampling-rate of 2.5 MS/s. The effectiveness of our neural recording system is validated in in-vivo recording of the primary somatosensory cortex of a rat.

• 전자공학회논문지S
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• 제35S권12호
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• pp.103-108
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• 1998

디지털 자기기록 장치에서의 용량의 증가는 필연적으로 심각한 인접 심벌간의 간섭 (Intersymbol interference : ISI)과 비선형 왜곡현사을 겪게된다. 본 논문에서는 디지털 자기기록 채널의 심각한 심벌간의 간섭과 비선형 왜곡현상을 보상해 주기 위한 방법으로 신경망을 이용한 등화기를 부분 삭제 모델로 나타난 자기기록 채널에 적용하였다. 신경망을 이용한 결정궤환 등화기 (Neural Decision Feedback Equalizer : NDFE)와 일반적인 결정궤환 등화기 (Decision Feedback Equalizer : DFE)간의 성능을 컴퓨터를 이용한 모의 실험을 통해 비교하였다. 실험 결과, 신경망을 이용한 결정궤환 등화기가 기존의 결정궤환 등화기보다 디지털 자기기록 장치에서 기록 밀도가 증가함에 따라 같은 신호 대 잡음비 (Signal-to-Noise Ratio : SNR)에서 우수한 비트 오류 확률 (bit error probability or bit error ratio : BER) 성능을 보였다.. 또한 같은 밀도의 경우에도 비선형 왜곡 현상이 강할수록 신경망을 이용한 결정궤환 등화기가 보다 안정적이며 우수한 성능을 보였다.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.1060-1071
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• 2014

Signals of the Electroencephalogram (EEG) can reflect the electrical background activity of the brain generated by the cerebral cortex nerve cells. This has been the mostly utilized signal, which helps in effective analysis of brain functions by supervised learning methods. In this paper, an approach for improving the accuracy of EEG signal classification is presented to detect epileptic seizures. Moreover, Independent Component Analysis (ICA) is incorporated as a preprocessing step and Short Time Fourier Transform (STFT) is used for denoising the signal adequately. Feature extraction of EEG signals is accomplished on the basis of three parameters namely, Standard Deviation, Correlation Dimension and Lyapunov Exponents. The Artificial Neural Network (ANN) is trained by incorporating Levenberg-Marquardt(LM) training algorithm into the backpropagation algorithm that results in high classification accuracy. Experimental results reveal that the methodology will improve the clinical service of the EEG recording and also provide better decision making in epileptic seizure detection than the existing techniques. The proposed EEG signal classification using feed forward Backpropagation Neural Network performs better than to the EEG signal classification using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier in terms of accuracy, sensitivity, and specificity.

• 센서학회지
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• 제24권1호
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• pp.22-28
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• 2015

This study demonstrates a polyimide nerve cuff electrode with a conductive polymer for improving recording signal quality at peripheral nerve. The nerve cuff electrodes with platinum (Pt), iridium oxide (IrOx), and poly(3,4-ethylenedioxythiophene): p-toluene sulfonate (PEDOT:pTS) were fabricated and investigated their electrical characteristics for improving recorded nerve signal quality. The fabricated nerve cuff electrodes with Pt, IrOx, and PEDOT:pTS were characterized their impedance and CDC by using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry. The impedance of PEDOT:pTS measured at 1 kHz was $257{\Omega}$, which was extremely lower than the value of the nerve cuff electrodes with IrOx ($15897{\Omega}$) and Pt ($952{\Omega}$), respectively. Furthermore, the charge delivery capacity (CDC) of the nerve cuff electrode with PEDOT:pTS was dramatically increased to 62 times than the nerve cuff electrode with IrOx. In ex-vivo test using extracted sciatic nerve of spaque-dawley rat (SD rat), the PEDOT:pTS group exhibited higher signal-to-interference ratio than IrOx group. These results indicated that the nerve cuff electrode with PEDOT:pTS is promising for effective implantable nerve signal recording.

• 대한의용생체공학회:의공학회지
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• 제21권5호
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• pp.477-485
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• 2000

본 논문에서는 신경신호기록을 위한 반도체 미세전극용 전치증폭기의 잡음특성을 설계하기 위한 체계적인 방법을 제시한다. 세포외기록(extracellular recording)에 의하여 측정된 신경신호와 전형적인 CMOS소자의 저주파 잡음특성을 함계 고려하여 전체 신호대잡음비를 계산하였다. 2단 CMOS 차동증폭기에 대한 해석과 함께 신호대잡음비에 중요한 영향을 끼치는 요소들에 대하여 설명하였다. 출력잡음전력에 대한 해석적인식을 유도하였으며 이로부터 회로설계자가 조절할 수 있는 주파수응답과 소자 파라미터들을 결정하였다. 입력소자의 크기와 트랜스컨덕턴스의 비가 최적영역으로부터 약간 벗어날 경우에 신호대잡음비가 크게 저하됨을 보였다. 이와 함께 만족스런 잡음특성을 위한 증폭이의 설계 변수 값들도 제시하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.31-34
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• 1997

A semiconductor microelectrode array has been successfully used in obtaining single unit recordings from medial giant nerve of clay fish, rat saphenous nerve and abdominal ganglia of aplysia. The recording device fabricated using silicon microfabrication techniques is a depth-probe type and, previously, has been mostly used to record from central nerve system of vertebrates. From invertebrates, and also from peripheral nerves of vertebrates, however, the quality of the recorded signal depends heavily on the recording conditions, such as the proximity of the electrode site to the nerve cells and the size of the neuron. We have modeled the signal to noise ratio as unctions of these parameters and compared the experimental data with the calculated values thus obtained.

• Journal of the Optical Society of Korea
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• 제18권2호
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• pp.174-179
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• 2014

Since in vitro neural recording and imaging applications based on a surface plasmon resonance (SPR) technique have expanded dramatically in recent years, cytotoxicity assessment to ensure the biosafety and biocompatibility for those applications is crucial. Here, we report the cytotoxicity of the SPR substrate incorporating a flint glass whose refractive index is larger than that of a conventional crown glass. A high refractive index glass substrate is essential in neural signal detection due to the advantages such as high sensitivity and wide dynamic range. From experimental data using primary hippocampal neurons, it is found that a lead-based flint glass is not appropriate as a neural recording template although the neuron cells are not directly attached to the toxic glass. We also demonstrate that the adhesion layer between the glass substrate and the gold film plays an important role in achieving the substrate stability and the cell viability.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.38-40
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• 2005

Microdrive with high precision and light mass enough to install on mouse head was fabricated for recording the reliable signal of neuron cell to understand the brain study. The proposed microdrive has three H-form PZT actuators and its guide structure. The microdrive operation principle is based on the well known inchworm principle. The synchronization of three PZT actuators is able to produce the linear motion along the guide structure. Our proposed microdrive has a precise accuracy of about 100nm and a long stroke of about 5mm. The electrode which is used for the recording of the action potential of the neuron cell was fixed at one of PZT actuators. The proposed microdrive was suited to acquisition of signals from in vivo extra-cellular single-unit recoding. On the condition of the anesthetized mouse, the single-unit signals could be recorded by using the proposed microdrive. In addition, applying the PZT microdrive to an alert mouse, we try to implant it on a mouse brain skull to explore single neuron firing.