• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.719-722
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• 2003

This paper describes a novel experiment that measures the skin movement of a hand based on MR (magnetic resonance) images in conjunction with surface modeling techniques. The proposed approach consists of 3 phases: (1) MR scanning of a hand with surface makers, (2) 3D reconstruction from the MR images. and (3) registration of the 3D models. The results of registration are used to trace the skin movement with respect to underlying bone motions by measuring the positions of the surface markers.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.642-645
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.269-272
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• 2009

The environment of Ubiquitous in terms of improvement is being expanded to various fields and time enabled system. Thus, a real-time spatial information management system has been developed by integrating a human movement detection system into a SICS(Spatial Information Control System) engine that can integrally manage inside spatial information extracted from 3D CAD and outside spatial information of GIS. The add-on program was developed to extract spatial information necessary for the SICS engine from 3D CAD information, and a human movement detection system was developed. Test bed was operated for 2weeks and indoor human flow information was found out by zone. Also, the direction of future research was decided through a test bed.

• 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.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.647-655
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• 2012

Objective: The purpose of this study was to confirm difference between angular foot movement time and existing foot Fitts' law predicting times, and to develop the angular foot Fitts' law in the foot tapping task. Background: Existing studies of foot Fitts' law focused on horizontal movement to predict the movement time. However, when driving a car, humans move their foot from the accelerator to the brake with a fixed heel. Therefore, we examined the experiment to measure angular foot movement time in reciprocal foot tapping task and compared to conventional foot Fitts' law predicting time. And, we developed the angular foot Fitts' law. Method: In this study, we compared the angular foot movement time in foot tapping task and the predicted time of four conventional linear foot Fitts' law models - Drury's foot Fitts' law, Drury's ballistic, Hoffmann's ballistic, Hoffmann's visually-controlled. 11 subjects participated in this experiment to get a movement time and three target degrees of 20, 40, and 60 were used. And, conventional models were calculated for the prediction time. To analyze the movement time, linear and arc distance between targets were used for variables of model. Finally, the angular foot Fitts' law was developed from experimental data. Results: The average movement times for each experiment were 412.2ms, 474.9ms, and 526.6ms for the 89mm, 172mm, and 253mm linear distance conditions. The results also showed significant differences in performance time between different angle level. However, all of conventional linear foot Fitts' laws ranged 135.6ms to 401.2ms. On the other hand, the angular foot Fitts' law predicted the angular movement time well. Conclusion: Conventional linear foot Fitts' laws were underestimated and have a limitation to predict the foot movement time in the real task related angular foot movement. Application: This study is useful when considering the human behavior of angular foot movement such as driving or foot input device.

• Journal of Acupuncture Research
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• v.30 no.1
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• pp.13-22
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• 2013

Objectives : The aim of this study was to show the application to add the Dong-Qi therapy of the Dong-Si acupuncture to exercise therapy of the movement system impairment syndrome(MSIS) and to determine the best acupuncture point for the Dong-Qi therapy. Methods : We reviewed Diagnosis and Treatment of Movement Impairment Syndrome and Movement System Impairment Syndromes Of The Extremities, Cervical and Thoracic Spines written by Sahrmann SA. to show the exercise therapy of the sort of MSIS. We reviewed complete works of Yang Wei Jie to show the acupuncture points of the Dong-Si acupuncture and the Dong-Qi therapy. Results : We showed the acupuncture point of the Dong-Si acupuncture by each type of MSIS based on the reference book of MSIS, the Dong-Si acupuncture. Also, we selected and tabulated the best possible acupuncture point of the Dong-Si acupuncture which could minimize a side effect of acupuncture during the therapeutic exercise by each type of MSIS. Conclusion : A specific acupuncture point of the Dong-Si acupuncture could be chosen for a specific MSIS therapeutic exercise. The best possible acupuncture point could be chosen when selecting an acupuncture point of the Dong-Si acupuncture.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.315-316
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• 2007

This paper presents a new methodology to improve movement database for a humanoid robot. The database is initially full of human motions so that the kinetics characteristics of human movement are immanent in it. then, the database is updated to the pseudo-optimal motions for the humanoid robot to perform more natural motions, which contain the kinetics characteristics of robot. for this, we use the evolutionary algorithm. the methodology consists of two processes : (1) the offline imitation learning of human movement and (2) the online generation of natural motion. The offline process improve the initial human motion database using the evolutionary algorithm and inverse dynamics-based optimization. The optimization procedure generate new motions using the movement primitive database, minimizing the joint torque. This learning process produces a new database that can endow the humanoid robot with natural motions, which requires minimal torques. In online process, using the linear combination of the motion primitive in this updated database, the humanoid robot can generate the natural motions in real time. The proposed framework gives a systematic methodology for a humanoid robot to learn natural motions from human motions considering dynamics of the robot. The experiment of catching a ball thrown by a man is performed to show the feasibility of the proposed framework.

• Korean Institute of Interior Design Journal
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• v.18 no.6
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• pp.124-132
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• 2009

Recently, 'Emotion' has attracted public attention socially and continuously in the fields such as construction, environment, design and products. Also, phenomenological concept of space through the physique in the viewpoint of the human-oriented aspect, namely, body, has been managed as a planned measure suitable for a new era and space. In this study, the author examined and analyzed the verbs and emotional vocabulary about the human body's behavior. The phenomenological space conception through body, i.e, flesh in this human centered point of view is being treated as the suitable planning measure on the new era and space. Though the epochal issue for Emotion is being attempted in many ways in various field such as product and marketing, the approach through the relationship between human and space. Therefore, we would like to see how the Emotion related to the movement that occurs in the space by analyzing the human body movement which is the subject of experiencing the space experimentally and research the characteristic of Emotion and space movement. SPSS 12.0 was used for the analysis to perform the analysis of basic statistics and Factor Analysis, and then to analyze the characteristic and emotional attribute for the experimental analysis. Comparing the activity for the 2 groups' behavior through the analyzed result with the test, active behavior was found to be higher than inactive behavior in the emotional value, and their bodies' motion showed averagely positive value in the emotional aspect; their bodies' motion was presented differently according to the attributes and amount of the people who would experience a specific space. However, the author found that affirmative and active behavior showed emotional aspect more than inactive behavior.

• Korean Journal of Human Ecology
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• v.13 no.3
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• pp.407-415
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• 2004

The purpose of this study was to investigate the effect of kindergarten's factors on athletic movement ability in early childhood. The factors included teacher's perception of athletic movement, length of time for physical activity, and number of athletic facilities in the kindergarten. The subjects consisted of 551 children aged from four to five years in 8 private kindergartens. The instruments used for this study were the obstacle course of Project Spectrum for measuring athletic movement ability, and the questionnaire to investigate the teacher's perception, length of time for physical activity, and number of athletic facilities in the kindergarten. The data from all the tests were analyzed by correlation and regression analyses. The results of this study exhibited that the length of time for physical activity was the most important factor among three factors, and the teachers' perception of athletic movement and the number of athletic facilities in the kindergarten were also deciding factors for the children's athletic movement ability.