• Biotechnology and Bioprocess Engineering:BBE
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• 제8권4호
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• pp.252-256
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• 2003

In this paper we describe the status of a silicon-based microelectrode for neural recording and an advanced neural interface. We have developed a silicon neural probe, using a combination of plasma and wet etching techniques. This process enables the probe thickness to be controlled precisely. To enhance the CMOS compatibility in the fabrication process, we investigated the feasibility of the site material of the doped polycrystalline silicon with small grains of around 50 nm in size. This silicon electrode demonstrated a favorable performance with respect to impedance spectra, surface topography and acute neural recording. These results showed that the silicon neural probe can be used as an advanced microelectrode for neurological applications.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2002년도 종합학술발표회 논문집 Vol.12 No.1
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• pp.366-369
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• 2002

Two artificial neural networks (ANN) are used to model the electric coupling probe in the combline resonators. One is used to analyze and synthesize the electric probe, and the other is used to correct errors between the results of the analysis and the synthesis ANNs and the fabrication results. The ANNs for the analysis and the synthesis of the electric probe are trained using the physical dimensions of the electric probe and the corresponding coupling bandwidth which is obtained using the finite element method. The ANNs for the error correction are trained using a very small set of the measurement results. Once trained, the ANN models provide the correct result approaching the accuracy of the measurement. The results from the ANN models show fairly good agreement with those of the measurement and they can be used as good initial design values.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1138-1143
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• 2015

Effects of fabrication process variations on impedance of microelectrodes integrated on a neural probe were examined through equivalent circuit modeling and SPICE simulation. Process variation and the corresponding range were estimated based on experimental data. The modeling results illustrate that the process variation induced by metal etching process was the dominant factor in impedance variation. We also demonstrate that the effect of process variation is frequency dependent. Another process variation that was examined in this work was the thickness variation induced by deposition process. The modeling results indicate that the effect of thickness variation on impedance is negligible. This work provides a means to predict the variations in impedance values of microelectrodes on neural probe due to different process variations.

• 센서학회지
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• 제20권1호
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• pp.19-24
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• 2011

Brain disorders such as epilepsy is a condition that affects an estimated 2.7 million Americans, 50,000,000 worldwide, approximately 200,000 new cases of epilepsy are diagnosed each year. Of the major chronic medical conditions, epilepsy is among the least understood. Scientists are conducting research to determine appropriate treatments, such as the use of drugs, vagus nerve stimulation, brain stimulation, and Peltier chip-based focal cooling. However, brain stimulation and Peltier chip-based stimulation processes cannot effectively stop seizures. This paper presents simulation of a novel heat enchanger network(HEN) technique designed to stop seizures by using a neural cooling probe to stop focal and spontaneous seizures by cooling the brain. The designed probe was composed of a U-shaped tube through which cold fluid flowed in order to reduce the temperature of the brain. The simulation results demonstrated that the neural probe could cool a 7 $mm^2$ area of the brain when the fluid was flowing atb a velocity of 0.55 m/s. It also showed that the neural cooling probe required 23 % less energy to produce cooling when compared to the Peltier chip-based cooling system.

• 마이크로전자및패키징학회지
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• 제16권2호
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• pp.33-42
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• 2009

뇌로부터 뉴런의 움직임을 탐지할 수 있는 폴리머 계열 기반의 유연한 뉴런 프로브가 개발되었다. 삽입 강도 증가를 위해서 5 ${\mu}m$ 두께의 생체 적합성이 우수한 금을 상하층 폴리머 사이에 전기도금 하였다. 개발된 뉴런 프로브는 실제 뇌 조직과 비슷한 강도를 지닌 젤에 조금의 균열도 없이 삽입되었다. 또한 기계적 잔류 스트레스 및 이로 인해 발생하는 뉴런 프로브의 휘어짐을 최소화하기 위하여 두 가지의 새로운 방법이 적용되었다; (1) 제작 완료 후 후열처리 과정을 통하여 잔류 스트레스를 최소화하는 방법 (2) 상하층을 서로 다른 물질로 제작하여 상호 간의 잔류 스트레스를 보상하는 방법. 위 두 가지의 방법을 적용한 후에는 제작된 직후 뉴런 프로브의 끝부분에서 보여졌던 휘어짐이 뚜렷하게 제거되었다. 전기적 특성 측정 결과 뉴런 프로브는 뇌로부터 뉴런의 신호를 기록하기에 적절한 임피던스 값을 가지고 있음을 보였으며 측정된 임피던스 값은 72시간 후에도 변함이 없었다. 또한 생체 외 신호 측정 실험 결과 제작된 프로브는 잔류 스트레스의 완전한 제거뿐만 아니라 우수한 신호 기록 능력을 보였다. 일주일 후에도 측정 결과에는 변함이 없었으며, 이는 제작된 전극이 생체 내에서 뉴런 파이어링(firing)으로부터 장기간의 안정적인 신호 기록의 가능성을 보인다고 할 수 있다.

• 전기학회논문지
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• 제56권11호
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• pp.1998-2003
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• 2007

A flexible but implantable polyimide-based neural implant was fabricated for reliable and stable long-term monitoring of neural activities from brain. The developed neural implant provides 3-dimensional (3D) $3{\times}3$ structure, avoids any hand handling, and makes the insertion more efficient and reliable. Any film curvature caused by residual stress was not observed in the electrode. The 3D flexible polyimide electrode penetrated a dense gel whose stiffness is close to live brain tissue, because a ${\sim}1{\mu}m$ thick nickel was electroplated along the edge of the shank in order to improve the stiffness. The recording sites were positioned at both side of the shank to increase the probability of recording neural signals from a target volume of tissue. Impedance remained stable over 72 hours because of extremely low moisture uptake in the polyimide dielectric layers. At electrical recording test in vitro, the fabricated electrode showed excellent recording performance, suggesting that this electrode has the potential for great recording from neuron firing and long-term implant performance.

• Journal of Welding and Joining
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• 제16권3호
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.

• 대한기계학회논문집A
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• 제24권5호
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• pp.1175-1182
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• 2000

Diffraction systematically causes error in acoustic measurements. Most probes are designed to reduce this phenomenon. On the contrary, this paper proposes a spherical probe a] lowing acoustic inten sity measurements in three dimensions to be made, which creates a diffracted field that is well-defined, thanks to analytic solution of diffraction phenomena. Six microphones are distributed on the surface of the sphere along three rectangular axes. Its measurement technique is not based on finite difference approximation, as is the case for the ID probe but on the analytic solution of diffraction phenomena. In fact, the success of sound source identification depends on the inverse models used to estimate inverse diffraction phenomena, which has nonlinear properties. In this paper, we propose the concept of nonlinear inverse diffraction modeling using a neural network and the idea of 3 dimensional sound source identification with better performances. A number of computer simulations are carried out in order to demonstrate the diffraction phenomena under various angles. Simulations for the inverse modeling of diffraction phenomena have been successfully conducted in showing the superiority of the neural network.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.147-148
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• 1998

In this paper, we developed the process for depth-probe type silicon microelectrode arrays. The process consists of four mask steps only. The steps are for defining sites, windows, and for shaping probe using plasma etch from above, and for shaping using wet etch from below, respectively. The probe thickness is controlled by dry etching, not by impurity diffusion. We used gold electrodes with a triple dielectric system consisting of oxide/nitride/oxide. The shank of the probe taper from 200um to tens of urn tip and has 30 um thickness.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.209-210
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• 1998

Noise characteristics of preamplifier, the most essential part of on-chip signal processing circuitry for the active semiconductor neural probe, is the important factor determining the overall signal-to-noise-ratio (SNR). We present a systematic design method for the optimization of SNR, based on the spectral characteristics of the electrode, circuit noise and extracelluar action potential. Analytical expression is derived to calculate total output noise power. Output SNR of 2-stage CMOS preamplifier is tailored to meet the given specification while the layout area is minimized.