• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.157-166
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• 2005

In 3D virtual environment the description of character' s movement that has utilized the conventional key-frame technique is gradually being developed toward the application of motion control method to generate more realistic and natural motion. Even the motion control method, however, has the limitation for expression of character's motion adapted to the ground properties of virtual world. That is, the walking motions of character are not only, for the most part, so uniform simple and repeated often as to feel to be tedious, but also the unnatural motion in which the tips of the toes soak through a plane or float in the air discording with the conditions of terrain lowers the semblance of reality. This paper proposes an adaptive motion control method for human figure locomotion in virtual environments or games, in which the walking motion is dynamiccally adapted to the ground's sliding properties. We compute an optimal parameters for one cycle of walking motion adapted to the ground properties by combining the coefficient of friction and centripetal force, and therefrom we induce a set of nonskid speed corresponding to various sliding properties of the ground.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1092-1101
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• 2003

Most of 3D character animation adjusts the gait of their characters for various terrains, using motion capture data through the motion capture equipments. This motion capture data can be naturally presented as real human motions, which are to be adjusted according to the various types of terrain. In addition, there would be a difficulty applying motion capture data for other characters in which the motion data will be captured again or edited for the existing motion data. Therefore, this paper proposes a method that is to generate walking motion for various terrains, such as flat, inclined plane, stair, and irregular face, and a method that is to calculate the trajectory of the swing leg and pelvis. These methods are able to generate various gaits controlled by the parameters of body height, walking speed, stride, etc. In addition, the positions and angles of joint can be calculated by using inverse kinematics, and the cubic spline will be used to calculate the trajectory of the joint.

• Korean Journal of Applied Biomechanics
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• v.30 no.4
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• pp.321-335
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• 2020

Objective: The purpose of this study was to investigate the effect of neck traction and foot type on plantar pressure distribution during walking. Method: Total of 24 data were collected from women working with a computer for more than 6 hours every day. Three groups by foot type were divided: Pes Planus, normal foot, and Pes Cavus. Depending on the foot type and cervical traction, plantar pressure variables were measured; CA, MF, PP, and CT. Each variable was divided into 12 masks. MANOVA was performed for the difference of plantar pressure variables by foot type, and a paired t-test was performed for the cervical traction within groups. Results: The total CA decreased in the Pes Planus (p<.001) and Pes Cavus (p<.05) groups. MF increased in the big toe (p<.01) and 2nd toe (p<.05) of the normal foot, and MF-3rd metatarsal decreased (p<.01). The MF-2nd toe (p<.01) and 3rd toe (p<.05) of Pes Cavus decreased. The PP decreased in 2nd toe (p<.05), 3rd toe (p<.01), and 4th toe (p<.05) of the Pes Cavus. In normal foot, the PP-3rd metatarsal (p<.05) and PP-4th metatarsal (p<.01) reduced. In Pes Planus, PP decreased in the hindfoot (p<.05). In Pes Cavus group wearing a neck-tractor, the CT-hindfoot increased (p<.05). Conclusion: There was a significant change in the plantar pressure change by foot type after neck traction. When walking with a neck-tractor, the heel impact was alleviated in the Pes Planus, and the Pes Cavus showed the smooth and effective propulsion in the push-off. Overall, weight acceptance was effectively performed when walking with neck-traction. It was also found that the neck-tractor corrects the alignment of the neck, thereby creating a more stable gait pattern.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.91-101
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• 2008

This paper proposes component-based density propagation for tracking a component-based human body model that comprises components and their flexible links. We divide a human body into six body parts as components - head, body, left arm, right arm, left foot, and right foot - that are most necessary in tracking its movement. Instead of tracking a whole body's silhouette, using component-based density propagation, the proposed method individually tracks each component of various parts of human body through a human body model connecting the components. The proposed human body tracking system has been applied to track movements usee for young children's movement education: balancing, hopping, jumping, walking, turning, bending, and stretching. This proposed system demonstrated the validity and effectiveness of movement tracking by independently detecting each component in the human body model and by acquiring an average 97% of high tracking rate.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.124-131
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• 2017

This paper present a novel approach to control the lower body power assistive exoskeleton system of a HEXAR-CR35 aimed at improving a muscular strength. More specifically the control of based on the human intention is crucial of importance to ensure intuitive and dexterous motion with the human. In this contribution, we proposed the detection algorithm of the human intention using the MCRS which are developed to measure the contraction of the muscle with variation of the circumference. The proposed algorithm provides a joint motion of exoskeleton corresponding the relate muscles. The main advantages of the algorithm are its simplicity, computational efficiency to control one joint of the HEXAR-CR35 which are consisted knee-active type exoskeleton (the other joints are consisted with the passive or quasi-passive joints that can be arranged by analyzing of the human joint functions). As a consequence, the motion of exoskeleton is generated according to the gait phase: swing and stance phase which are determined by the foot insole sensors. The experimental evaluation of the proposed algorithm is achieved in walking with the exoskeleton while carrying the external mass in the back side.

• Journal of Biomedical Engineering Research
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• v.28 no.3
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• pp.377-386
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• 2007

Mechanical loading to bone cells using simple sine wave or constant wave fluid flow has been widely used for in vitro experiments. Human gait is characterized by a complex loading to bones of lower extremities which results from a series of events consisting of heel strike, foot flat and push-off during the stance phase of the gait cycle. Telemetric force analyses have shown that human femora are subject to multiphasic loading. Therefore, it would be ideal if the physiologic loading conditions during human walking can be used for in vitro mechanotransduction studies. Here, for a mechanotransduction study, we develop it fluid flow system (FFS) in order to simulate human physiologic mechanicalloading on bone cells. The development methods of the FFS including the COR (Center for Orthopedic Research), monitor program are presented. The FFS could generate various multiphasic loading conditions of human gaits with output flow. Wall shear distribution was very uniform, with 81 % of the effective loading area of the culture on a glass slide. Our results demonstrated that the FFS, provide a new translational approach for unveiling molecular mechanotransduction pathways in bone cells.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.179-185
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• 2014

In this paper, a quadruped walking pet robot for human-robot interaction, a robot-controller using a smart phone application program, and a home smart control system using sensor informations providing from the robot are described. The robot has 20 degree of freedom and consists of various sensors such as Kinect sensor, infrared sensor, 3 axis motion sensor, temperature/humidity sensor, gas sensor and graphic LCD module. We propose algorithms for the robot entertainment: walking algorithm of the robot, motion and voice recognition algorithm using Kinect sensor. emotional expression algorithm, smart phone application algorithm for a remote control of the robot, and home smart control algorithm for controlling home appliances. The experiments of this paper show that the proposed algorithms applied to the pet robot, smart phone, and computer are well operated.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.631-638
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• 2012

This work proposes a new method to generate velocity profile of a traction motor equipped in a rehabilitation system for knee joint patients through humanoid robot simulation. To this end, a three-dimensional full-body humanoid robot model is newly constructed, and natural human gait is simulated by applying to it reference joint angle trajectories already published. Linear velocity is derived from distance data calculated between the positions of a thigh band and its traction motor at every sampling instance, which is a novel idea of this paper. The projection rule is employed to kinematically describe the humanoid robot because of its high efficiency and accuracy, and measured joint trajectories are used in simulating human natural gait referring to Winter's book. The attained motor velocity profile for a certain position in human body will be applied to our walking-assistance system which is implemented with a treadmill system.