• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.891-894
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• 2005

This paper describes a human finger model driven by shape memory alloy(SMA) wires. The finger model has three joints that are similar to human finger. Each joint is actuated with two wires in the antagonistic manner and six wires are used to actuate three finger joint. In order to obtain the desirable finger motion, the diameters of the SMA wires are designed with different diameters by considering the required actuating force and response time. The rotary sensors are used to measure the angle positions of the joints and PWM control using PID algorithm is used to achieve desired angle positions of the finger joints. After estimating the control performance of each finger joint for the desired angle position, the antagonistic motion control of the finger model is experimentally evaluated.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.217-226
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• 2006

Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

• 대한인간공학회지
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• 제26권2호
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• pp.149-155
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• 2007

Recently, various devices requiring text input such as mobile phone IPTV, PDA and UMPC are emerging. The frequency of text entry for them is also increasing. This study was focused on the evaluation of Korean text entry interface. Various models to evaluate text entry interfaces have been proposed. Most of models were based on human cognitive process for text input. The cognitive process was divided into two components; visual scanning process and finger movement process. The time spent for visual scanning process was modeled as Hick-Hyman law, while the time for finger movement was determined as Fitts' law. There are three questions on the model-based evaluation of text entry interface. Firstly, are human cognitive processes (visual scanning and finger movement) during the entry of text sequentially occurring as the models. Secondly, is it possible to predict real text input time by previous models. Thirdly, does the human cognitive process for text input vary according to users' text entry speed. There was time gap between the real measured text input time and predicted time. The time gap was larger in the case of participants with high speed to enter text. The reason was found out investigating Eye-Hand Coordination during text input process. Differently from an assumption that visual scan on the keyboard is followed by a finger movement, the experienced group performed both visual scanning and finger movement simultaneously. Arrival Lead Time was investigated to measure the extent of time overlapping between two processes. 'Arrival Lead Time' is the interval between the eye fixation on the target button and the button click. In addition to the arrival lead time, it was revealed that the experienced group uses the less number of fixations during text entry than the novice group. This result will contribute to the improvement of evaluation model for text entry interface.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.544-547
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• 2008

As the mobile electronic product is getting slimmer and smaller, the necessity of keypad is being increased. But the possibility of mis-typing keypad is increased rapidly due to the integrated keypad in the small mobile product. The business division has not considered the methodology of keypad design essentially. In this paper, analysis method and design evaluation standard to reduce the mis-typing of UMPC(Ultra Mobile Personal Computer) is suggested. First, the finite element analysis model and the biomechanical human body model are implemented in order to simulate the exact contact characteristic between finger and keypad. The reliability of analysis model is guaranteed by the comparison of the contact pressure between analysis result and experiment result of the pressure sensor. The design optimization of key shape and layout is derived through the response surface method. The prototype model is produced with the optimized design of keypad, and then it verified the advanced function with user mis-typing detection test. The optimized keypad design reduced the mis-typing ratio from 35% of existing model to 75 of proposed model. If this paper is widely applied to not only UMPC but also the other electronic products, the emotional quality of all products could be improved considerably.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권12호
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• pp.780-788
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• 2008

손 포즈 모델링 및 추적은 컴퓨터 시각 분야에서 어려운 문제로 알려져 있다. 손 포즈 3차원 복원을 위한 방법에는 사용되는 카메라의 수에 따라 다중 카메라 또는 스테레오 카메라 기반 방식과 단일카메라 기반 방식이 있다. 다중 카메라의 경우 여러 대의 카메라를 설치하거나 동기화를 시키는 등에 대한 제약사항이 따른다. 본 논문에서는 확률 그래프 모델에서 신뢰 전파 (Belief Propagation) 알고리즘을 이용하여 단안 카메라에서 획득된 2차원 입력 영상으로부터 3차원 손 포즈를 추정하는 방법을 제안한다. 또한, 은닉 마르코프 모델(Hidden Markov Model)을 인식기로 하여 손가락 클릭 동작을 인식한다. 은닉 노드로 손가락의 관절 정보를 표현하고, 2차원 입력 영상에서 추출된 특징을 관측 노드로 표현한 확률 그래프 모델을 정의한다. 3차원 손 포즈 추적을 위해 그래프 모델에서의 신뢰 전파 알고리즘을 이용한다. 신뢰 전파 알고리즘을 통해 3차원 손 포즈를 추정 및 복원하고, 복원된 포즈로부터 손가락의 움직임에 대한 특징을 추출한다. 추출된 정보는 은닉 마르코프 모델의 입력값이 된다. 손가락의 자연스러운 동작을 위해 본 논문에서는 한 손가락의 클릭 동작 인식에 여러 손가락의 움직임을 함께 고려한다. 제안한 방법을 가상 키패드 시스템에 적응한 결과 300개의 동영상 테스트 데이타에 대해 94.66%의 높은 인식률을 보였다.

• 대한인간공학회지
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• 제28권3호
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• pp.1-6
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• 2009

Recently, importance of the rehabilitation of hand pathologies as well as the development of high-technology hand robot has been increased. The biomechanical model of hand is indispensable due to the difficulty of direct measurement of muscle forces and joint forces in hands. In this study, a three-dimensional biomechanical model of four fingers including three joints and ten muscles in each finger was developed and a mathematical relationship between neural commands and finger forces which represents the enslaving effect and the force deficit effect was proposed. When pressing a plate under the flexed posture, the muscle forces and the joint forces were predicted by the optimization technique. The results showed that the major activated muscles were flexion muscles (flexor digitorum profundus, radial interosseous, and ulnar interosseous). In addition, it was found that the antagonistic muscles were also activated rather than the previous models, which is more realistic phenomenon. The present model has considered the interaction among fingers, thus can be more powerful while developing a robot hand that can totally control the multiple fingers like human.

• 로봇학회논문지
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• 제7권1호
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• pp.1-8
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• 2012

A humanoid robot hand with one thumb and two fingers has been developed. Each finger has the specially designed compact joints, called "MEC Joint", which convert the rotation of a motor to the swing motion of a pendulum. The robot hand with the MEC Joints is compact and relatively light but strong enough to grasp objects in the same manner as human being does in daily activities. In this paper the kinematic model and the torque characteristics of the MEC Joint are presented and compared with the results of the dynamic simulation and the dynamometer test. The dynamic behavior of the thumb and two fingers with MEC Joints are also presented by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.124-129
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• 1992

The goal of the proposed Intelligent Assisting System - IAS is to assist human operators in an intelligent way, while leaving decision and goal planning instances for the human. To realize the IAS the very important issue of manipulation skill identification and analysis has to be solved, which then is stored in a Skill Data Base. Using this data base the IAS is able to perform complex manipulations on the motion control level and to assist the human operator flexibly. We propose a model for manipulation skill based on the dynamics of the grip transformation matrix, which describes the dynamic transformation between object space and finger joint space. Interaction with a virtual world simulator allows the calculation and feedback of appropriate forces through controlled actuators of the sensor glove with 10 degrees-of-freedom. To solve the sensor glove calibration problem, we learn the nonlinear calibration mapping by an artificial neural network(ANN). In this paper we also describe the experimental system setup of the skill acquisition and transfer system as a first approach to the IAS. Some simple manipulation examples and simulation results show the feasibility of the proposed manipulation skill model.

• 한국산업정보학회논문지
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• 제25권2호
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• pp.129-136
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• 2020

손가락 움직임 인식을 통한 제어는 직관적인 인간-컴퓨터 상호작용 방법의 하나이다. 본 연구에서는 여러 가지 ML (Machine learning) 기법을 사용하여 효율적인 손가락 움직임 인식을 위한 웨어러블 디바이스를 구현한다. 움직임 인식을 위한 시계열 데이터 분석에 전통적으로 사용되어 온 HMM (Hidden markov model) 및 DTW (Dynamic time warping) 기법뿐만 아니라 NN (Neural network) 기법을 적용하여 손가락 움직임 인식의 효율성 및 정확성을 비교하고 분석한다. 제안된 시스템의 경우, 경량화된 ML 모델을 설계하기 위해 각 ML 기법에 대해 최적화된 전처리 프로세스를 적용한다. 실험 결과, 최적화된 NN, HMM 및 DTW 기반 손가락 움직임 인식시스템은 각각 99.1%, 96.6%, 95.9%의 정확도를 제공한다.

• 대한인간공학회지
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• 제32권2호
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• pp.179-187
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• 2013

Objective: The purpose of this study is to extract GOMS manual operator, except for an experiment with participants. Background: The GOMS model has advantage of rapid modeling which is suitable for the environment of technology development which has a short life cycle products with a fast pace. The GOMS model was originally designed for desktop environment so that it is not adequate for implementing into the latest HCI environment such as small touch screen device. Therefore, this research proposed GOMS manual operator extraction methodology which is excluded experimental method. And flick Gesture was selected to explain application of proposed methodology to extract new operator. Method: Divide into start to final step of hand gesture needed to extract as an operator through gesture task analysis. Then apply the original GOMS operator to each similar step of gesture and modify the operator for implementation stage based on existing Fitts' law research. Steps that are required to move are modified based on the Fitts' law developed in touch screen device. Finally, new operator can be derived from using these stages and a validation experiment, performed to verify the validity of new operator and methodology by comparing human performance. Results: The average movement times of the participants' performance and the operator which is extracted in case study are not different significantly. Also the average of movement times of each type of view study is not different significantly. Conclusion: In conclusion, the result of the proposed methodology for extracting new operator is similar to the result of the experiment with their participants. Furthermore the GOMS model included the operator by the proposed methodology in this research could be applied successfully to predict the user's performance. Application: Using this methodology could be applied to develop new finger gesture in the touch screen. Also this proposed methodology could be applied to evaluate the usability of certain system rapidly including the new finger gesture performance.