• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.862-868
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• 2007

The planar motion of the index finger in general human hands is usually implemented by the actuation of three joints. This task requires a technique to determine the joint combination for each fingertip position which is well-known as the inverse kinematics problem in robotics. Especially, it is an essential work for grasping and manipulation tasks by robotic and humanoid fingers. In this paper, an intelligent neural learning scheme for solving such inverse kinematics is presented. Specifically, a multi-layered neural network is utilized for effective inverse kinematics, where a dynamic neural learning algorithm is employed for fast learning. Also, a bio-mimetic feature of general human fingers is incorporated to the learning scheme. The usefulness of the proposed approach is verified by simulations.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.327-328
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• 2008

로봇과 상호 작용하기 위한 수단으로 손동작 인식 시스템이 많이 사용되고 있으며, 본 논문에서는 손에 부가적인 장치를 장착하지 않은 상태에서 영상 처리를 이용하여 손동작을 인식하는 시스템을 구현하였다. 먼저 로봇은 영상 입력 장치로써 웹캠을 사용하고, 손 영상을 스킨 컬러를 바탕으로 영상 처리를 하여 추출해내고, 그 이미지를 분석하여 그 모양이 가위인지 바위인지 보인지 인식한다. 가위 바위 보 게임을 위하여 로봇이 손동작을 표현할 수 있도록 손가락이 네 개인 손을 설계 및 구현하였다. 이때, 기존의 와이어 방식이 아닌 제어를 이용한 손가락을 설계하였고, 각각의 손가락이 독립적으로 제어될 수 있기 때문에 가위 바위 보의 손동작을 표현할 수 있다. 그리고 음성 인식을 이용하여 사람과 동시에 가위 바위 보 중 하나를 결정한 후 표현하기 때문에 가위 바위 보 게임이 가능하다. 뿐만 아니라 로봇이 승패도 알 수 있다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.2
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• pp.125-133
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• 2017

This paper presents the inter-rater reliability of finger spasticity assessment tested realized by using finger simulator that mimics finger spasticity of patients after a stroke. For controlling the simulator torque, finger spasticity was modeled, and the model parameters were obtained by measuring quantitative data while grading based on Modified Ashworth Scale (MAS). A robotic finger simulator was designed for mimicking finger spasticity. Evaluation of this simulator with the help of seven rehabilitation doctors showed that the simulator had a Cohen's kappa value of 0.619 for Metacarpophalangeal Joint and 0.514 for Proximal Interphalangeal Joint. Fleiss' kappa between raters is 0.513 for Metacarpophalangeal Joint and 0.486 for Proximal Interphalangeal Joint. Therefore, the spasticity assessment made by MAS grade system is not reliable owing to the subjectivity of the assessment. The proposed robotic simulator can be used as a training tool for improving the reliability of the spasticity assessment.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.709-716
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• 2013

Rehabilitation of finger patients requires that the patients exercise their hands and fingers for proper functioning to return. A thumb rehabilitation robot, equipped with a two-axis force sensor, can prevent injury to the thumb by monitoring the applied pulling force. In this paper, we describe a link-type thumb rehabilitation robot designed for patients' thumb rehabilitation exercise. Tests of the manufactured link-type thumb rehabilitation robot were performed on normal male patients. Our results show that the robot can be used for flexibility and muscle-strength rehabilitation exercises for a patient's thumb.

• ICROS
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• v.22 no.1
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• pp.17-23
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• 2016

본 기술 특집호에서는 개인용 탑승시스템(PMS, Personal Mobility System) 혹은 이동로봇을 무선 원격 제어할 때 사용할 수 있는 인터페이스(지자기센서 기반형, 조그셔틀형)들을 소개하고, 사용자 편리성 제어 기반으로 인터페이스 방식을 분석한다. 지자기센서 기반의 절대방향 제어는 자기북극을 기준으로 한 지자기센서의 측정값인 방향각을 이용하여 스마트폰의 방향각에 탑승시스템의 방향각을 같도록 탑승시스템을 제어하는 것이다. 탑승시스템에 서있는 탑승자가 스마트폰을 이용하여 탑승시스템이 원하는 방향으로 이동하기 위하여 제어할 때에는 스마트폰의 화면에 표시되어진 시작 버튼에 손가락을 놓고, 원하는 방향으로 스마트폰을 좌 우로 회전시키면 탑승시스템은 그 방향으로 회전을 하며 주행한다. 터치기반의 조그셔틀 인터페이스를 이용하여 원하는 방향으로 이동하기 위해서는 탑승시스템에 서있는 사용자가 스마트폰의 화면에 표시되어진 조그셔틀 스위치에 손가락을 놓고, 원하는 방향대로 손가락을 움직이면 스마트폰은 블루투스 무선통신을 통하여 탑승시스템을 주행 할 수 있다.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.5
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• pp.516-523
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• 2012

Stroke patients should exercise for the rehabilitation of their fingers, because they can't use their hand and fingers. The moving direction of thumb of five fingers is different that of four fingers (force finger, middle finger, ring finger, little finger). The thumb rehabilitation robot for rehabilitation exercise must be included a force control system, because robot can injure thumb by applying too much force. In this paper, the rectangular-type thumb rehabilitation robot was developed for stroke patient's thumb rehabilitation exercise of the flexibility rehabilitation exercise. The characteristic test of the developed rectangular-type thumb rehabilitation robot was carried out with normal men in their twenties. As a result, it is thought that the robot can be used for the flexibility rehabilitation exercise of stroke patient's thumb.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.196-199
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• 2010

본 논문에서는 영상처리 기능을 통해 손 제스처를 인식하는 알고리즘을 개발하고 이를 활용하여 로봇의 움직임을 원격으로 제어하는 시스템을 구현하였다. 전체 시스템은 손 영상을 획득하는 카메라, 영상처리를 수행하는 컴퓨터, 그리고 LEGO Mindstorm 로봇으로 구성되며, 컴퓨터와 로봇 사이의 통신은 Mindstorm에 내장된 블루투스 기능을 사용하였다. 카메라에서 획득한 영상에서 사람의 손에 해당하는 영역만을 추출하기 위해 먼저 컬러 필터링을 수행하였으며 영상의 신뢰성을 향상시키기 위해 잡음을 제거하는 보정 작업을 거친다. 그리고 무게중심 연산을 통해 손의 중심점을 추정하고 이로부터 일정 거리에 있는 손가락 영역을 추출한다. 마지막으로 펼쳐진 손가락 개수를 구하고 그 개수에 따라 미리 설정된 명령을 로봇에 전송한다. 실험을 통해 조명 상태가 양호하고 배경이 복잡하지 않은 대부분의 환경에서 로봇 원격제어가 성공적으로 이루어짐을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.341-347
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• 2013

This study presents the remote control of a board robot using a Sensing glove based on Bluetooth communication. The board robot is a kind of riding robot controlled by an user. The user wears the proposed remote glove controller, and changes a direction of the robot by different kinds of finger actions. Bluetooth is used for wireless communication between the board robot and its user. CdS cell Sensors and a LED in the glove are used for recognition of a number of finger actions, which are measured as analog signals. The finger actions have five commands ('1'right '2'neutrality '3'left '4'operation '5'stop), which are transmitted from the user to the board robot through Bluetooth communication. Experimental results show that proposed a Sensing glove can effectively control the board robot.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.139-146
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• 2020

The disadvantage of the general robot cleaner is that it works only on the designated route, so it is impossible to clean the place outside the designated route. Therefore, in this study, the direction control methodology for searching the place other than the designated route based on the finger recognition technology was studied to compensate for the shortcomings of the existing cleaner. Raspberry Pi was used as the main controller and Open CV program was used to recognize the number of fingers. To verify the validity of the proposed methodology, a finger recognition algorithm was implemented using Python language, and as a result of adopting the Logitech C922, the success rate was 100% at 90cm and 70% at 110cm, respectively.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.4
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• pp.233-238
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• 2014

In this paper, we developed a finger robot simulating spasticity and contracture which can be used as a testing bed for evaluating performance of hand rehabilitation devices while it can be also used to train clinicians for improving reliability of clinical assessment. The robot is designed for adult finger size and for independent control of Metacarpophalangeal Joint and Proximal Interphalangeal Joint. Algorithm for mimicking spasticity and contracture is implemented. By adjusting the parameters related to contracture and spasticity, the robot can mimic various patterns of responses observed in fingers with spasticity and contracture.