• Korean Journal of Applied Biomechanics
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• v.25 no.3
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• pp.257-263
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• 2015

Objective : The purpose of this study was to investigate the effect of genu valgum on the body mass index, movement of lower limb joints, and ground reaction force. Methods : Gait patterns of 30 college students with genu valgum were analyzed and the static Q angle of the femur was measured for selecting genu valgum of the subjects. To analyze the kinetic changes during walking, the six-camera Vicon MX motion analysis system was used. The subjects were asked to walk 12 meters using the more comfortable walking method for walking. After they walked 12 meters more than 10 times, their most natural walking patterns were chosen three times and analyzed. Results : As a result of measuring a relationship between genu valgum and Q-angle, as the Q-angle increases, it showed a genu valgum also increased. Body Mass Index showed a significant difference between the groups was higher in the genu valgum group.(p<.001). The analysis result showed that genu valgum had a significant effect on the internal rotation moment in the hip joint(p<.05). Also, genu valgum had a significant effect on the internal rotation moment of the knee joint(p<.05). The comparative analysis of the Medial-Lateral ground reaction force in the genu valgum group showed a tendency to increase the medial ground reaction force(p<.05). The vertical ground reaction forces of the middle of the stance phase(Fz0) showed a significant increase in genu valgum group(p<.05), in particular the results showed a decrease in the early stance phase(p<.001). Conclusion : In conclusion, the change in body mass is considered to be made by proactive regular exercise for improvement of the genu valgum. In addition, the prevention of the deformation caused by secondary of the genu valgum in this study may be used as an indicator of the position alignment rehabilitation for structural and functional improvements. Applying a therapeutic exercise program for the next lap will require changes in posture alignment.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.405-417
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• 2020

Due to the popularization of the Extended Reality, research is actively underway to implement human motion in real-time 3D animation. In particular, Microsoft developed Kinect cameras for 3D motion information can be obtained without the burden of facilities and with simple operation, real-time animation can be generated by combining with 3D formats such as FBX. Compared to the marker-based motion capture system, however, Kinect has low accuracy due to its lack of estimated performance of joint information. In this paper, two algorithms are proposed to correct joint estimation errors in order to realize natural human motion in motion capture animation system in Kinect camera-based FBX format. First, obtain the position information of a person with a Kinect and create a depth map to correct the wrong joint position value using the human body segment length constraint information, and estimate the new rotation value. Second, the pre-set joint motion range constraint is applied to the existing and estimated rotation value and implemented in FBX to eliminate abnormal behavior. From the experiment, we found improvements in human behavior and compared errors between algorithms to demonstrate the superiority of the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.151-158
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• 2019

Patients with disabilities from various reasons such as disasters, injuries or chronic illness or elderly with limited body motion range due to aging are recommended to participate in rehabilitation programs at hospitals. But typically, it's not as simple for them to commute without help as they have limited access outside of the home. Also, regarding the perspectives of hospitals, having to maintain the workforce and have them take care of the rehabilitation sessions leads them to more expenses in cost aspects. For those reasons, in this paper, a home-based remote rehabilitation system using motion recognition is developed without needing help from others. This system can be executed by a personal computer and a stereo camera at home, the real-time user motion status is monitored using motion recognition feature. The system tracks the joint range of motion(Joint ROM) of particular body parts of users to check the body function improvement. For demonstration, total of 4 subjects with various ages and health conditions participated in this project. Their motion data were collected during all 3 exercise sessions, and each session was repeated 9 times per person and was compared in the results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1244-1248
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• 2003

This paper describes visual tracking procedure of the underwater mobile robot for nuclear reactor vessel inspection, which is required to find the foreign objects such as loose parts. The yellowish underwater robot body tends to present a big contrast to boron solute cold water of nuclear reactor vessel, tinged with indigo by Cerenkov effect. In this paper, we have found and tracked the positions of underwater mobile robot using the two color information, yellow and indigo. The center coordinates extraction procedures are as follows. The first step is to segment the underwater robot body to cold water with indigo background. From the RGB color components of the entire monitoring image taken with the color CCD camera, we have selected the red color component. In the selected red image, we extracted the positions of the underwater mobile robot using the following process sequences; binarization, labelling, and centroid extraction techniques. In the experiment carried out at the Youngkwang unit 5 nuclear reactor vessel, we have tracked the center positions of the underwater robot submerged near the cold leg and the hot leg way, which is fathomed to 10m deep in depth.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.217-222
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• 1995

We propose some applications of image processing techniques to extract quantitative measurements by using a camera system developed in Korea university and Catholic Medical School. From now on the system will be called as KCMOTION. The purpose of this study is to provide basic kinematic and kinetic data for the analysis of human movements and to find the clinical usefulness and reliability of the proposed motion analysis system. Two tests, sit-to-stand (STS) movements and pendulum test, are conducted by the system. The aims of the tests are to identify variability and reliability of KCMOTION to give some quantitative comparisons to the other systems. The result of STS movement are compared to the LOCUS IIID motion analyzer by the ratio of maximum flexion movement per body weight to the actual maximum flexion extension torque per body weight. That result in 29 % and 33 % for hip and knee joint, respectively in KCMOTION and 27 % and 30 % in LOCUS IIID System. The results of the pendulum movements are compared to that of using Cybex and Electrogoniometer with relaxation index, amplitude ratio, swing number and swing time. The results of relaxation index and amplitude ratio of the KCMOTION are between those of the Cybex and Electrogoniometer. We also observed that the KCMOTION detect more natural movement, from the results of swing number and time.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.475-480
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• 2008

In this paper, I will propose a Custom-made Suit Production System. The system does not only help the customers to edit and measure their size by creating the landmarks in the 2D human body images which is taken from the camera, but it also visualizes the virtual cloth by using the landmarks and the modeling data of the virtual cloth. In this system is a new technology for the digital and the automation which is not handmade way of using Custom-made Suit industry. It will be generally useful in the various contents of the clothing industry.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.24-29
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• 2014

This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.

• Journal of Korean Institute of Industrial Engineers
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• v.9 no.2
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• pp.9-25
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• 1983

The purpose of this study was to film up computerized analyses for both kinematic posture(film analysis) and muscle dynamics (EMG) during a weight-lifting motion. (Snatch, Clean and Jerk) Using a motor drive camera (3.5 frames/sec) and a Location Analyzer, motion tracks of 13 landmarks, which were attached to the major joints, during the motion were converted into digital values. At the same time, EMG amplitudes from 11 major muscle groups were recorded. Recorded data were processed via analog/hybrid computer (ADAC 480) and digital computer (PDP 11/44). Landmark locations and EMG amplitude were integrated by a computerized routine. Computer output included graphic reproductions on sepuential dislocations of body segments, center of gravity of body segments and the associated changes on EMG amplitude such as % EMG's of major muscle group during a weight lifting motion. The results strongly suggest that the computerized motion-EMG integration can provide a further working knowledge in selection and in training of workers and athletes. Suggestions for a further study include additional device for velocity measurement, expansion of the link model for biomechanical analysis and other implementations necessary for athletic application.