• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.91-102
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• 2016

This study classified the lower body types of female adults aged 18 to 69. The lower body was divided into front, lateral front, and lateral back. In order to understand the shape and somatotype of each segment, 592 people were analyzed based on girth, height, length, depth, width, angle and cross section distance for each segment. For data analysis, SPSS 18.0 was performed for descriptive statics, principal component analysis, K-means cluster analysis, ANOVA, and Duncan's test (as verification). Factor analysis was performed based on index values, calculation values, angles, and cross section distances. The measured items resulted in a.) 16 items were extracted to 5 factors in the case of the front factor (FF) of the lower body, and b.) 24 items were extracted to 6 factors in the case of lateral front factor (LFF) and lateral back factor (LBF). Each factor was put through K-means cluster analysis, classifying the lower bodies into one of four types of based on the front type (FT), the lateral front type (LFT), and the lateral back type (LBT) respectively. This study proposed an understanding of various lower body shapes by segmenting and classifying the lower body shapes for each type.

• Korean Journal of Head & Neck Oncology
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• v.21 no.2
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• pp.190-195
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• 2005

Background and Objectives: Fibula is the flap of choice for reconstruction of wide mandible defects after tumor ablation surgery. In mandible reconstruction, restoring the mandible frame to provide mandibular contour and dental arch while restoring masticatory function are important. Even though vascularized fibula can be osteotomized freely, proper design and flap insetting is not easy because of its three dimensional structure and difference in design according to the defect sites. We reviewed patients who underwent mandible reconstruction with fibular flaps according to the defect sites and suggest proper modification methods of fibular flap according to the various defects sites after tumor ablation surgery. Materials and Methods: Twelve consecutive mandible reconstruction with fibular free flaps were performed for defects after tumor ablation surgery. Patients were classified into 4 groups according to the type of mandibular defect(Group 1 : defect on central segment including symphysis, Group 2 : defect on lateral segment(with or without central segment) confined to body, Group 3 : defect on body and ascending ramus that does not include the condyle, Group 4 : defect including the condyle). Results: We suggest different modification methods of fibular free flap for each patient group. Group 1, 3 ; contour by using multiple closing wedge osteotomy. Group 2 ; single or double barrel reconstruction without wedge osteotomy. Group 4 ; contour using single or multiple wedge osteotomy and condylar reconstruction with costochondral graft. Conclusion: Fibular free flaps can be contoured to any desired shape after multiple osteotomies to restore various mandibular defects. It is a reliable and versatile method for reconstruction of mandibular defects after tumor ablation surgery.

• Korean Journal of Applied Biomechanics
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• v.15 no.1
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• pp.45-61
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• 2005

Stance is defined as any state in which the total mass of the body is supported by the feet. In order to maintain stance, the sum of gravito-inertial forces acting on the body must be registered by equal and opposite forces at the region of contact between the organism and the support surface. Balance is controlled by applying forces to the surface of support so as to maintain the body's center of mass vertically above the feet. for a muIti-segment organism, there can be a variety of ways in which balance can be controlled, since movements of different body segments can have similar effects on the control of balance. In general, the organism tends to have a body configuration that is aligned with gravito-inertial force when there are no external forces acting on it. If any segments of the body are not aligned with gravito-inertial force vector, a torque on that segment would tend to move the body's center of mass. The maintenance of postural stability is accomplished in humans by a complex neural control system. This requires organizing integrating and acting upon visual, vestibular, and somatosensory input, providing orientation information to the postural control system. The information necessary to control and coordinate movement is provided by the visual sense of eye position with respect to the surrounding surface layout, the vestibular sense of head orientation in the gravito-inertial space, and the somatic sense of body segment position relative to one another and to the support surface. In this study, perception and action capability was examined from various points of view. The underlying assumption of the study was that the change of postural configuration could be effected by organism, environment and task goal.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of Sensor Science and Technology
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• v.31 no.3
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• pp.156-162
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• 2022

This study estimates the relative position between body segments using segment orientation and segment-to-joint center (S2J) vectors. In many wearable motion tracking technologies, the S2J vector is treated as a constant based on the assumption that rigid body segments are connected by a mechanical ball joint. However, human body segments are deformable non-rigid bodies, and they are connected via ligaments and tendons; therefore, the S2J vector should be determined as a time-varying vector, instead of a constant. In this regard, our previous study (2021) proposed a method for determining the time-varying S2J vector from the learning dataset using a regression method. Because that method uses a deformation-related variable to consider the deformation of S2J vectors, the optimal variable must be determined in terms of estimation accuracy by motion and segment. In this study, we investigated the effects of deformation-related variables on the estimation accuracy of the relative position. The experimental results showed that the estimation accuracy was the highest when the flexion and adduction angles of the shoulder and the flexion angles of the shoulder and elbow were selected as deformation-related variables for the sternum-to-upper arm and upper arm-to-forearm, respectively. Furthermore, the case with multiple deformation-related variables was superior by an average of 2.19 mm compared to the case with a single variable.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.77.2-77
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• 2002

Human upright standing posture in the sagittal plane is studied, when it exposed in the antero-posterior vibration. A two link inverted pendulum model is considered and described its functional behavior in terms of ankle and hip joint according to the dominant joints that provides the largest contribution to the corresponding human reactionary motion. The data is analyzed, both in the time domain and the frequency domain. Subjects behave as a non-rigid pendulum with a mass and a spring throughout the whole period of the platform motion. When vision was allowed, each segment of body shows more stabilized.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.6
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• pp.502-508
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• 2012

An analytical model for a human body is important to predict muscle and joint forces. Because it is difficult to estimate muscle or joint forces from a human body, the objective of this study is the development of a reliable analytical model for a human body to evaluate the lower extremity muscle and joint forces. The musculoskeletal system of the human lower extremity is modeled as a multibody system employing the Hill-type muscle model. Muscle forces are determined to minimize energy consumption, and we assume that motion is constrained in the sagittal plane. Muscle forces are calculated through an equilibrium analysis while rising from a seated position. The musculoskeletal model consists of four segments. Each segment is a rigid body and connected by frictionless revolute joints. Muscles of the lower extremity are simplified to seven muscles with those that are not related to the sagittal plane motion are ignored. Muscles that play a similar role are combined together. The results of the present study are compared with experimental results to validate the lower extremity model and the assumptions of the present study.

• Korean Journal of Applied Biomechanics
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• v.16 no.4
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• pp.13-20
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• 2006

A platform diving with categorizing 624C motion was video taped and 3D kinematic variables were analyzed. This motion is consist of 3 parts from the headstand position to the act of turning after take-off. The results indicated that it took a very short time from the moment of take-off to the act of 1/2 turning because the turning motion has already started from preparing motion even before the fingertips have parted from the ground. Also, there was barely any jumping height due to the use of upper limbs segment and there was little difference in the moving distance compared to the standing events judging from horizontal movement of 1.1m. The horizontal velocity of the center of human body was increased before take-off while the vertical velocity was decreased right after take-off and the velocity of lower limbs segment was faster than the upper limbs segment showing contrary results to the standing events. In the aspects of angular velocity, the upper limbs segment starts the turning motion when take-off by rapidly extending its angular velocity while lower limbs segment make large angular velocity even before take-off.

• Korean Journal of Applied Biomechanics
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• v.12 no.1
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• pp.233-249
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• 2002

The purpose of this study was to employing MRI in the estimation of the biomechanical body segment parameters of Korean adults. for this purpose MRI study on 19 Korean living subjects were used to measurement. All the parameters that was concerned were inertial characteristics of human body mass of each segment, center of mass of them and the length of radius of gyration of them. The cross sectional images and saggital images of every 1cm interval were got using the 0.5 Tesla MRI from the top of head to the bottom of foot, whole body. And then, by tracing the images of the film and scanning them, got the area which the several tissues occupied in the image of slice. By summing the area of slice of each segment which were calculating and by multipling the density of the tissues, got the mass of segment and other inertial characteristics. The ratios of radius of gyration in both transverse axis and longitudinal axis though the segmental mass and segment length are as follow: male A : head($0.229\pm0.0029$), neck($0.256\pm0.0095$), thorax($0.374\pm0.0059$) abdomen($0.245\pm0.0020$), pelvis($0.368\pm0.0106$), thigh($0.288\pm0.0030$) shank($0.280\pm0.0043$), foot($0.277\pm0.0195$), upperarm($0.311\pm0.0074$) forearm($0.286\pm0.0051$), hand($0.253\pm0.0095$) female A : head($0.214\pm0.0032$), neck($0.254\pm0.0112$), thorax($0.295\pm0.0061$) abdomen($0.289\pm0.0021$), pelvis($0.329\pm0.0108$), thigh($0.288\pm0.0036$) shank($0.280\pm0.0047$), foot($0.243\pm0.0206$), upperarm($0.279\pm0.0083$) forearm($0.286\pm0.0048$), hand($0.229\pm0.0097$) male B : head($0.532\pm0.0006$), neck($0.533\pm0.0006$), thorax($0.658\pm0.0008$) abdomen($1.350\pm0.0022$), pelvis($0.875\pm0.0002$), thigh($0.213\pm0.0001$) shank($0.160\pm0.0001$), foot($0.152\pm0.0002$), upperarm($0.136\pm0.0002$) forearm($0.202\pm0.0002$), hand($0.273\pm0.0006$) female B : head($0.198\pm0.0002$), neck($0.335\pm0.0011$), thorax($0.238\pm0.0001$) abdomen($0.888\pm0.0001$), pelvis($1.318\pm0.0117$), thigh($0.095\pm0.0001$) shank($0.075\pm0.0001$), foot($0.181\pm0.0006$), upperarm($0.0.062\pm0.0001$) forearm($0.083\pm0.0001$), hand($0.105\pm0.0007$).