• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.23-29
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• 2023

In this paper, we introduce a method to obtain high-quality results at a low cost for simulating musculoskeletal characters based on data from the reference motion through motion capture on two-legged walking through reinforcement learning. We reset the motion data of the reference motion to allow the character model to perform, and then train the corresponding motion to be learned through reinforcement learning. We combine motion imitation of the reference model with minimal metabolic energy for the muscles to learn to allow the musculoskeletal model to perform two-legged walking in the desired direction. In this way, the musculoskeletal model can learn at a lower cost than conventional manually designed controllers and perform high-quality bipedal walking.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.54-64
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• 2005

The study investigated genetic algorithms for the optimal control model of maximum height vertical jumping. The model includes forward dynamic simulations by the neural excitation-control variables. Convergence of genetic algorithms is very slow. In this paper the micro genetic algorithm(micro-GA) was used to reduce the computation time. Then a near optimal solution from micro-GA was an initial solution for VF02, which is one of well-developed and proven nonlinear programming algorithms. This approach provided the successful optimal solution for maximum-height jumping without a reasonable initial guess.

• Journal of the KSME
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• v.53 no.8
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• pp.34-37
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• 2013

이 글에서는 인체 근골격 동역학 모델을 이용하여, 인체 관절 내부의 하중을 예측하고 관절 질환의 원인을 분석하는 방법에 대한 최근 연구를 소개하고자 한다.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.7 s.196
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• pp.133-138
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• 2007

It is important to understand the characteristics of amputee gait to develop more advanced prostheses. The aim of this study was quantitatively to analyze the stair climbing task for the above-knee amputee with a prosthesis and to predict muscle forces and joint moments at musculoskeletal joints by dynamic analysis. The three-dimensional musculoskeletal model of lower extremities was constructed by gait analysis and transformation software for one above-knee amputee and ten healthy people. The measured ground reaction forces and kinematical data of each joint by gait analysis were used as input data during inverse dynamic analysis. Lastly, dynamic analysis of above-knee amputee during stair climbing were performed using musculoskeletal models. The results showed that summed muscle farces of hip extensor of amputated leg were greater than those of sound leg but the opposite results were revealed at hip abductor and knee flexor of amputated leg. We could also find that the higher moments at hip and knee joint of sound leg were needed to overcome the flexion moment caused by body weight and amputated leg. In conclusion, dynamic analysis using musculoskeletal models may be a useful mean to predict muscle forces and joint moments for specific motion tasks related to rehacilitation therapy..

• CDE review
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• v.18 no.2
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• pp.38-46
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• 2012

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.16-23
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• 2005

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.2
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• pp.73-78
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• 2020

Musculoskeletal disease is often caused by sitting down for long period's time or by bad posture habits. In order to prevent musculoskeletal disease in daily life, it is the most important to correct the bad sitting posture to the right one through real-time monitoring. In this study, to detect the sitting information of user's without any constraints, we propose posture measurement system based on multi-channel pressure sensor and CNN model for classifying sitting posture types. The proposed CNN model can analyze 5 types of sitting postures based on sitting posture information. For the performance assessment of posture classification CNN model through field test, the accuracy, recall, precision, and F1 of the classification results were checked with 10 subjects. As the experiment results, 99.84% of accuracy, 99.6% of recall, 99.6% of precision, and 99.6% of F1 were verified.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1554-1559
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• 2003

This study validated the musculoskeletal model of the human lower extremity by comparative study between calculated muscle parameters through simulation using modified hill-type model and measured them through isokinetic exercise. And the relationship between muscle forces and moments participated in motion was quantified from the results of simulation. For simulation of isokinetic motion, a three-dimensional anatomical knee model was constructed using trials of gait analysis and the EMG-force model was used to determine muscle activation level exciting muscles. The modified Hill-type model was used to calculate individual muscle forces and moments in dynmaic analysis and the results were validated by comparing them of experiments on BIODEX. The results showed that there was a high correlation between calculated torques from simulation and measured them from experiments for isokinetic motion(R=0.97). Therefore we concluded that the simulation by using musculoskeletal model was so useful means to predict and convalesce musculoskeletal-related diseases, and analyze unrealizable experiment such as clash condition.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.7-15
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• 2005

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.1015-1016
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• 2010