• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.359-363
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• 2004

Numerous studies have been performed to analyze various phenomena of human's walking, gait. In the present study, unrecognized walking and recognized walking were analyzed by three dimensional motion capture system(VICON motion system Ltd., England) and simulated by computer program. Two normal males participated in measuring the motion of unrecognized and recognized walking. Six infrared cameras and four force plates were used and sixteen reflective markers were attached to the subject to capture the motion. A musculoskeletal model was generated anatomically by using ADAMS(MSC software corp., USA) and LifeMOD(Biomechanics Research Group Inc, USA). The inverse dynamic simulation and forward dynamic simulation were also performed. The result of simulation was similar to the experimental result. This study provides the base line for dynamic simulation of the falling walking. It will be useful to simulate various another pathologic gaits for old peoples.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.485-493
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• 1999

Human can generate various posture and motion with nearly 350 muscle pairs. From the viewpoint of mechanisms, the human skeleton mechanism represents great kinematic and dynamical complexity. Physical and behavioral fidelity of human motion requires dynamically accurate modeling and controling. This paper describes a mathematical modeling, and dynamic simulation of human body. The human dynamic model is simplified as a rigid body consisting of 18 actuated degrees of freedom for the real time computation. Complex kinematic chain of human body is partitioned as 6 serial kinematic chains that is, left arm, right arm, support leg, free leg, body, and head. Modeling is developed based on Newton-Euler formulation. The validity of proposed dynamic model, which represents mathematically high order differential equation, is verified through the dynamic simulation.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1095-1102
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• 2014

In this paper, We proposed the approach of GPU and motion vector to analysis the Human activity in real-time surveillance system. The most important part, that is detect blob(human) in the foreground. We use to detect Adaptive Gaussian Mixture, Weighted subtraction image for salient motion and motion vector. And then, We use motion vector for human activity analysis. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Position Moving, Fixed Moving}, {Walking, Running}. We created approximately 300 conditions for the simulation. As a result, We showed a high success rate about 86~98%. The results also showed that the high resolution experiment by the proposed GPU-based method was over 10 times faster than the cpu-based method.

• Journal of Biomedical Engineering Research
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• v.31 no.2
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• pp.141-150
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• 2010

The purpose of this study was to analyze the golf swing motion for a soft golf clubs and regular golf club. Soft golf is a newly developed recreational sports for all ages, including the elderly and the beginners of golf. To quantify the effect of using soft golf club, which much lighter club than regular clubs, a motion analysis has been performed using a 3D optoelectric motion tracking system that utilizes active infrared LEDs and near-infrared sensors. The subject performed swing motion using a regular golf club and a soft golf club in turn. The obtained motion capture data was used to build a 3D computer simulation model to obtain left wrist, elbow shoulder and lumbar joint force and torque using inverse and forward dynamics calculations. The joint force and torque during soft golf swing were lower than regular golf swing. The analysis gave better understanding of the effectiveness of the soft golf club.

• IE interfaces
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• v.17 no.1
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• pp.22-32
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• 2004

The most complicated and difficult area in the simulation of evacuation process is the area of human behavior. However, it is generally very difficult to understand and quantify human behaviors since the factors involved vary significantly according to the types of accidents and the environment. The walking speed of passenger is especially affected by dynamic effect and list due to damage and ship motion in wave. There are various methods to get the useful data for evacuation simulation. The onboard experimental approach is one of the strongest method. This paper discusses the onboard experimental results of human mobility of passengers in evacuation from ship. To realize ship trim and heel due to maritime casuality, the passage model for experiment is made. The experiment was carried out at dynamic and static condition respectively using the ship with passage model. The result was evaluated and it will be reflected in evacuation simulation tool.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.250-257
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• 1999

Driving simulators are used effectively for human factor study, vehicle system development and other purposes by enabling to reproduce actural driving conditions in a safe and tightly controlled enviornment. Interactive simulation requries appropriate sensory and stimulus cuing to the driver . Sensory and stimulus feedback can include visual , auditory, motion, and proprioceptive cues. A fixed-base driving simulator has been developed in this study for vehicle system developmnet and human factor study . The simulator consists of improved and synergistic subsystems (a real-time vehicle simulation system, a visual/audio system and a control force loading system) based on the motion -base simulator, KMU DS-Ⅰ developed for design and evaluation of a full-scale driving simulator and for driver-vehicle interaction.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.434-441
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• 2004

In this paper, an exoskeleton-type motion capturing system is designed and implemented. The device is designed to have 12 degree-of-freedom entirely to represent human arm motions. Forward and inverse kinematics of the device are analyzed to make sure of its singular positions. With the designed model parameters, simulation studies are conducted to verify that the designed motion capturing system is effective to represent human motions within the workspace. As a counterpart of the exoskeleton system, a mobile robot is built to follow human motion restrictively. Experimental studies of teleoperation from the exoskeleton device to control the mobile robot are carried out to show feasible application of wireless man-machine interface.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1038-1046
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• 2008

This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated bγ the motion imitation teaming. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion teaming based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements far a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.