• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.285-293
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• 2017

Jump rope has two motions. It starts as hand motion and ends as jump motion. Therefore, two motions should be considered together to detect rotations accurately. But previous researches only consider one of the two motions as in push-up, sit-up, lift dumbbells etc, which results in inaccurate detection of rotations. In this paper, detection of rotation in jump rope using two motions through 6-axis accelerometer gyro sensor is proposed. Jump motion is detected using accelerometer sensor and hand motion is detected using gyro sensor. Also start point and end point of jump rope is detected using magnitude and standard deviation of accelerometer and gyro sensor values. The count of rotation is detected using y-axis of gyro sensor value. Y-axis of gyro sensor value indicate hand motion of jump rope motion. The usefulness of the proposed method is confirmed through experimental results.

• Structural Engineering and Mechanics
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• v.87 no.5
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• pp.431-450
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• 2023

In this study, it is intended to perform nonlinear time-history analyses of nuclear power plant structures (NPP) under near-fault earthquakes showing directivity pulse and fling-step characteristics. Simulation procedures based on cycloidal pulse and far-fault ground motions are also used to simulate near-fault motions showing forward-directivity and fling-step characteristics and the structural responses are compared with those of the recorded near-fault ground motions. Because it is aimed to determine specifically the pulse type characteristics of near-fault ground motions on NPPs, all the ground motions are normalized to have a PGA of 0.3 g. Depending on the obtained results it can be underlined that although near-fault ground motion has the potential to cause damage mostly on structural systems having larger periods, it may also have noticeable effects on the responses of rigid structures, like NPP containment buildings. On the other hand, simulated near-fault motions can help us to get an insight into the near-fault mechanism as well as an approximate visualization of the structural responses under near-fault earthquakes.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.80-84
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• 2010

Tracking hands is an essential technique for hand gesture recognition which is an efficient way in Human Computer Interaction (HCI). Recently, many researchers have focused on hands tracking using a 3D hand model and showed robust tracking results compared to using 2D hand models. In this paper, we propose a novel 3D hand tracking method based on a coupled particle filter. This provides robust and fast tracking results by estimating each part of global hand poses and local finger motions separately and then utilizing the estimated results as a prior for each other. Furthermore, in order to improve the robustness, we apply a multi-cue based method by integrating a color-based area matching method and an edge-based distance matching method. In our experiments, the proposed method showed robust tracking results for complex hand motions in a cluttered background.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.625-633
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• 2006

Spatial variability of ground motions has significant influence on dynamic response of longitudinal structures such as bridges and tunnels. The coherency function, which quantifies the degree of positive or negative correlation between two ground motions, is often used to describe the spatially variable ground motions. This paper compares two available procedures for developing spatially variable ground time histories from a given coherency function. Hao's method shows serious limitation, resulting in unrealistic decrease in coherency with increase in distance Abrahamason's method, on the other hand, preserves important characteristics of the reference ground motion. Therefore, the Abrahamason's method is recommended to be used in developing spatially varying ground motions.

• Journal of IKEEE
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• v.24 no.4
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• pp.1039-1049
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• 2020

Neural decoding is important to recognize the user's intention for controlling a neuro-prosthetic hand. This paper proposes a real-time decoding method for multi-channel peripheral neural activity. Peripheral nerve signals were measured from the median and radial nerves, and motion artifacts were removed based on locally fitted polynomials. Action potentials were then classified using a k-means algorithm. The firing rate of action potentials was extracted as a feature vector and its dimensionality was reduced by a self-organizing feature map. Finally, a multi-layer perceptron was used to classify hand motions. In monkey experiments, all processes were completed within a real-time constrain, and the hand motions were recognized with a high success rate.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2126-2131
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• 2005

Interactions of a humanoid with a human are important, when the humanoid is requested to provide people with human-friendly services in unknown or uncertain environment. Such interactions may require more complicated and human-like behaviors from the humanoid. In this work the arm motions of a human are discussed as the early stage of human motion imitation by a humanoid. A motion capture system is used to obtain human-friendly arm motions as references. However the captured motions may not be applied directly to the humanoid, since the differences in geometric or dynamics aspects as length, mass, degrees of freedom, and kinematics and dynamics capabilities exist between the humanoid and the human. To overcome this difficulty a method to adapt captured motions to a humanoid is developed. The geometric difference in the arm length is resolved by scaling the arm length of the humanoid with a constant. Using the scaled geometry of the humanoid the imitation of actor's arm motions is achieved by solving an inverse kinematics problem formulated using optimization. The errors between the captured trajectories of actor arms and the approximated trajectories of humanoid arms are minimized. Such dynamics capabilities of the joint motors as limits of joint position, velocity and acceleration are also imposed on the optimization problem. Two motions of one hand waiving and performing a statement in sign language are imitated by a humanoid through dynamics simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.51.5-51
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• 2002

In this paper, we propose and developed a keyglove using the touch-typing method as new solutions to the problem of text input into the mobile computing devices. This device recognizes that character is typed in though the hand's movements analysis and requires no additional space on a person's desktop or work surface, and can be easily used with computers of any size, even the smallest mobile computer, and is designed as an input device for wearable computers and virtual environment. The concept of the wearable input device based on human hand-molies recognition.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2283-2286
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• 2003

This paper has expressed human's motion data into orthogonal parameters in low dimension, and created new motion data through this. We have reconstructed a new model consisting of orthogonal parameters from dividing human body data into three parts - hand, leg, and body to make new motions. Mixing these parts of body from different motions has leaded to new good motion data. It will be possible to use this motion editing not only for Animation Technology, but also for a three dimensional gesture recognition skill.

• Journal of Mechanical Science and Technology
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• v.17 no.2
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• pp.230-238
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• 2003

In this paper, a three-fingered anthropomorphic robot hand, called SKK Robot Hand 1, is presented. By employing a two-DOF joint mechanism, called Double Active Universal Joint (abbreviated as DAUJ from now on) as its metacarpal joint, the hand makes it possible to mimic humanlike motions. We begin with addressing the motivation of the design and mention how the anthropomorphic feature of a human is realized in the design of SKK Hand I Also, the mechanism of the hand is explained in detail, and advantages in its modular design are discussed. The proposed hand is developed for use as a testbed for dextrous manipulation. It is expected to resolve the increasing demand for robotic applications in unstructured environments. We describe its hardware construction as well as the controller structure including the preliminary results of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.62-69
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• 2008

A specialized anthropomorphic robot hand which can be attached to the biped humanoid robot MAHRU-R in KIST, has been developed. This built-in type hand consists of three fingers and a thumb with total four DOF(Degrees of Freedom) where the finger mechanism is well designed for grasping typical objects stably in human's daily activities such as sphere and cylinder shaped objects. The restriction of possible motions and the limitation of grasping objects arising from the reduction of DOF can be overcome by reflecting a typical human finger's motion profile to the design procedure. As a result, the developed hand can imitate not only human hand's shape but also its motion in a compact and efficient manner. Also this novel robot hand can perform various human hand gestures naturally and grasp normal objects with both power and precision grasping capability.