Neural Interface with a Silicon Neural Probe in the Advancement of Microtechnology

Oh, Seung-Jae,Song, Jong-Keun,Kim, Sung-June The Korean Society for Biotechnology and Bioengine 2003 Biotechnology and Bioprocess Engineering Vol.8 No.4

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.

손동작을 이용한 인간친화형 증강현실 인터페이스

최준영,서병국,박종일 한양대학교 우리춤연구소 2009 우리춤과 과학기술 Vol.5 No.1

기존의 증강현실을 위한 비전 기반 인터페이스는 대부분 환경적인 제약을 받거나,특수한 장비 혹은 복잡한 모델을 요구하기 때문에, 사용자에게 불편함을 주거나 실시간 동작이 힘들었다. 예를 들어, 마커를 이용하면 구현상의 편의성과 정확성을 보장하지만,일반적으로 마커는 환경과 대비되는 모양을 가지기 때문에, 사용자에게 거부감을 줄 수 있으며 무엇보다 복잡한 인터랙션에는 적용되기 힘들다. 본 논문은 증강현실을 위한 비전 기반 인터페이스로서 손동작을 제안한다. 손동작을 이용할 경우, 자연스럽고 다양한 인터랙션을 수행할 수 있지만, 손동작을 정확히 인식하는 일은 쉽지 않다. 이로 인해 지금까지 제안된 방법을 증강현실 시스템에 적용하는 데는 한계가 있다. 본 논문에서는 기본적으로 손동작을 이용한 인터페이스를 제안하는데,손동작 인식을 위한 알고리즘을 효율적으로 개선함으로써 , 복잡한 환경에서 적은 연산량으로 자연스러운 인터랙션을 제공하고자 한다. 제안된 인터페이스는 손의 자연스러운 움직임을 감지해서 손의 모양과 동작에 따라서 가상의 물체를 자연스럽게 제어할 수 있도록 해 준다. 다양한 환경에서의 실험 및 사용자 평가를 통해 제안된 인터페이스의 유용성을 검증하였다. A number of augmented reality interfaces have been developed for past decades, which used to have environmental or ergonomic limitation by requiring 3-D hand model or tracking hardware such as data glove. For example, even though maker-based interfaces guarantee accuracy and convenience in implementation, the maker may be visually intrusive to user, because a maker has distinct of shape and color from the scene. Moreover, it is difficult to provide natural (usually complicated) user interactions using makers. On the other hand, interface based on gesture recognition can provide natural user interactions, but the recognition rate is usually low. This paper proposes an efficient hand gesture recognition method and a natural AR interface using the method. The proposed method can provide natural interaction to users with less computational cost. It also achieves a greatly enhanced recognition rate of hand gestures by using a color band. The color information of the color band put on user's wrist extracts the hand-region in a fast and accurate manner. User can freely control virtual object using the proposed interface. For example, virtual objects can be shown up in the area where the user is pointing, can be handled and disappeared as the user controls. We verify the effectiveness of our interface by comparing with a maker-based AR interface through user evaluation.

인공신경망을 이용한 USB 인식 시스템

우세형(Sae-Hyeong Woo),박지수(Jisu Park),은성배(Seongbae Eun),차신(Shin Cha) 한국정보통신학회 2022 한국정보통신학회 종합학술대회 논문집 Vol.26 No.1

IoT 디바이스의 Plug & Play를 위하여 IoT 디바이스의 대표적인 유선 인터페이스인 USB의 종류를 이미지를 통하여 인식하는 모듈을 개발한다. IoT 디바이스를 구동시키기 위해서는 통신 및 디바이스 하드웨어를 구동하기 위한 드라이버가 필요하다. IoT 디바이스에 연결되는 유선 인터페이스를 스마트폰의 카메라 촬영을 통하여 얻은 이미지를 이용하여서 해당 통신 인터페이스를 인식한다. 대표적인 유선 인터페이스인 USB에 대하여 인공신경망 기반의 기계학습을 통하여 USB의 종류를 분류한다. 인공신경망의 충분한 학습을 위하여 인터넷을 통하여 USB 이미지를 수집하고, 이미지 처리를 통하여 추가적인 이미지 데이터 셋을 확보한다. 합성곱 신경망과 더불어서 다양한 심층 인공신경망으로 인식기를 구한하여서 그 성능을 비교, 평가한다. For Plug & Play of IoT devices, we develop a module that recognizes the type of USB, which is a typical wired interface of IoT devices, through image recognition. In order to drive an IoT device, a driver for communication and device hardware is required. The wired interface for connecting to the IoT device is recognized by using the image obtained through the camera of smartphone shooting to recognize the corresponding communication interface. For USB, which is a most popular wired interface, types of USB are classified through artificial neural network-based machine leaning. In order to secure sufficient data set of artificial neural networks, USB images are collected through the Internet, and additional image data sets are secured through image processing. In addition to the convolution neural networks, recognizers are implemented with various deep artificial neural networks, and their performance is compared and evaluated.

자이로 센서와 인공신경망을 이용한 장애인용 컴퓨터

안용식,엄광문,김철승,허지운,나유진 대한의용생체공학회 2003 의공학회지 Vol.24 No.5

This paper aims at developing 'gyro-mouse' which provides decent and comfortable human-computer interface that supports the usage of such software as an internet-browser in PC for the people paralyzed in upper limbs. This interface operates on information collected from head movement to get the cursor control. The interface is composed of two modules. One is hardware module in which the head horizontal and vertical angular velocities are detected and transmitted into PC. The other is a PC software that translates the received data into movement and click signals of the mouse. The ANN (artificial neural network) learns the quick nodding pattern of each user as click input so that it can provide user-friendly interface. The performance of the system was evaluated by three indices that are click recognition rate. error in cursor position control. and click rate of the moving target box. The performance result of the gyro-mouse was compared with that of the optical-mouse to assess the efficiency of the gyro-mouse. The average click recognition rate was 93%, average error in cursor position control was 1.4∼5 times of optical mouse. and the click rate with 50 pixels target box was 40%(30 clicks/min) to that of optical mouse. The click rate increased monotonously with the number of trial from 35% to 44%. The suggested system is expected to provide a new possibility to communicate with the society. 본 연구에서는 교통사고나 뇌졸중 등에 의해 상지의 장애를 가지는 장애인을 대상으로 하여, 인터넷의 브라우저와 같은 소프트웨어를 사용 할 수 있도록 하는 컴퓨터 인터페이스를 구현하는 것을 목적으로 한다. 이 인터페이스는 커서를 제어하기 위해 머리 움직임의 정보를 이용한다. 실제 시스템은 머리의 수평, 수직 각속도를 검출하여 컴퓨터로 전송하는 하드웨어부분과, 전송 받은 신호를 처리하여 마우스의 움직임과 클릭신호로 변환하는 소프트웨어 부분으로 구성하였다. 클릭신호는 순간적인 끄덕임으로 정의하였으며 특히, 인공신경망이 각 사용자별 클릭 패턴을 학습하여 사용자 친화적인 인터페이스를 제공하도록 하였다. 구현된 시스템의 성능을 클릭의 인식률, 커서의 이동제어오차, 이동출현하는 목표박스의 단위시간당 클릭율의 세가지 항목으로 평가하였다. 또한. 일반적으로 사용되는 광마우스와 본 연구에서 개발한 자이로마우스를 각각 이 실험에 사용하여, 양자간의 차이를 비교하였다. 개발된 자이로마우스에서 클릭의 인식률은 평균 93%였고, 커서의 수평수직 이동 제어오차는 광마우스의 1.4∼1.5배였다. 랜덤위치에 출현하는 50픽셀의 목표박스의 클릭률은 광마우스의 40% (30 클릭/분)의 성능을 보였으며, 시행횟수에 따라 증가하여 l회차의 35%에서 3회차에는 44%로 단조증가하는 경향을 보였다. 제안된 시스템은, 장애인에게 사회와 의사소통 할 수 있는 새로운 가능성을 제시할 것이 기대된다.

신경망을 적용한 지체장애인을 위한 근전도 기반의 자동차 인터페이스 개발

곽재경(Jaekyung Kwak),전태웅(Taewoong Jeon),박흠용(Humyong Park),김성진(Sungjin Kim),안광덕(Kwangdek An) 한국IT서비스학회 2008 한국IT서비스학회지 Vol.7 No.2

  As the computing landscape is shifting to ubiquitous computing environments, there is increasingly growing the demand for a variety of device controls that react to user’s implicit activities without excessively drawing user attentions. We developed an EMG-based car interface that enables the physically handicapped to drive a car using their functioning peripheral nerves. Our method extracts electromyogram signals caused by wrist movements from four places in the user’s forearm and then infers the user’s intent from the signals using multi-layered neural nets. By doing so, it makes it possible for the user to control the operation of car equipments and thus to drive the car. It also allows the user to enter inputs into the embedded computer through a user interface like an instrument LCD panel. We validated the effectiveness of our method through experimental use in a car built with the EMG-based interface.

Quantitative Control of Neuron Adhesion at a Neural Interface Using a Conducting Polymer Composite with Low Electrical Impedance

Kim, Sung Yeol,Kim, Kwang-Min,Hoffman-Kim, Diane,Song, Hyun-Kon,Palmore, G. Tayhas R. American Chemical Society 2011 ACS APPLIED MATERIALS & INTERFACES Vol.3 No.1

<P>Tailoring cell response on an electrode is essential in the application of neural interfaces. In this paper a method of controlling neuron adhesion on the surface of an electrode was demonstrated using conducting polymer composite as an electrode coating. The electrodeposited coating was functionalized further with biomolecules-of-interest (BOI) with their surface concentration controlled via repetition of carbodiimide chemistry. The result was an electrode surface that promoted localized adhesion of primary neurons the density of which could be controlled quantitatively via changes in the number of layers of BOI added. Important to neural interfaces, it was found that additional layers of BOI caused an insignificant increase in the electrical impedance, especially when compared to the large drop in impedance upon coating of the electrode with conducting polymer composite.</P>

Wireless Neural Interface를 위한 인체통신 송수신기

육범진,김병설,배준성 한국통신학회 2020 한국통신학회 학술대회논문집 Vol.2020 No.11

Constitutive law for wedge-tendon gripping interface in anchorage device - numerical modeling and parameters identification

Marceau, D.,Fafard, M.,Bastien, J. Techno-Press 2003 Structural Engineering and Mechanics, An Int'l Jou Vol.15 No.6

Mechanical anchorage devices are generally tested in the laboratory and may be analyzed using the finite element method. These devices are composed of many components interacting through diverse contact interfaces. Generally, a Coulomb friction law is sufficient to take into account friction between smooth surfaces. However, in the case of mechanical anchorages, a gripping system, named herein the wedge-tendon system, is used to anchor the prestressing tendon. The wedge inner surface is made of a series of triangular notches designed to grip the tendon. In this particular case, the Coulomb law is not adapted to simulate the contact interface. The present paper deals with a new constitutive contact/gripping law to simulate the gripping effect. A parameter identification procedure, based on experimental results as well as on a finite element/neural network approach, is presented. It is demonstrated that all parameters have been selected in a satisfactory way and that the proposed constitutive law is well adapted to simulate the wedge gripping effect taking place in a mechanical anchorage device.

Graphene: an emerging material for biological tissue engineering

Sang Kyu Lee,Hyun Kim,Bong Sup Shim 한국탄소학회 2013 Carbon Letters Vol.14 No.2

Graphene, a carbon crystal sheet of molecular thickness, shows diverse and exceptional properties ranging from electrical and thermal conductivities, to optical and mechanical qualities. Thus, its potential applications include not only physicochemical materials but also extends to biological uses. Here, we review recent experimental studies about graphene for such bioapplications. As a prerequisite to the search to determine the potential of graphene for bioapplications, the essential qualities of graphene that support biocompatibility, were briefly summarized. Then, direct examples of tissue regeneration and tissue engineering utilizing graphenes, were discussed, including uses for cell scaffolds, cell modulating interfaces, drug delivery, and neural interfaces.

Electro-optical Neural Platform Integrated with Nanoplasmonic Inhibition Interface

Yoo, Sangjin,Kim, Raeyoung,Park, Ji-Ho,Nam, Yoonkey American Chemical Society 2016 ACS NANO Vol.10 No.4

<P>Engineering of neural interfaces with rianomaterials for remote manipulation facilitates the development of platforms for the study and treatment of brain disorders, yet extending their capability to inhibiting the electrical activities of unmodified neurons has been difficult. Here we report the development of an electro-optical neural platform integrated with gold nanorods for simultaneous electrical excitation and readout, and photothermal inhibition of neural activities. A monolayer of gold nanorods was placed at the electrode neuron interfaces of a microelectrode array for photothermal stimulation of neural activities. This nanoplasmonic interface interacted well with neurons and metal electrodes without affecting the biological and electrical properties. We demonstrated that spontaneous firing of neurons and their signal propagation along the neurites evoked by electrical stimulation were optically inhibited on this neural platform. We believe that our platform could be an alternative to the optogenetic approach and may ultimately be applied to prosthetic devices based on optical neuromodulation.</P>