• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.494-499
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• 2011

This paper presents the biomechanical analysis and evaluation technology of musculoskeletal system by multi-body human dynamic model and 3-D motion capture data. First, medical image based geometric model and material properties of tissue were used to develop the human dynamic model and 3-D motion capture data based motion analysis techniques were develop to quantify the in-vivo joint kinematics, joint moment, joint force, and muscle force. Walking and push-up motion was investigated using the developed model. The present model and technologies would be useful to apply the biomechanical analysis and evaluation of human activities.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1437-1438
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• 2013

• Journal of the Korean Society for Precision Engineering
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• v.24 no.12
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• pp.29-35
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• 2007

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.293-301
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• 2001

A patient-specific musculoskeletal model, whose parameters can be identified noninvasively, was developed for the automatic generation of patient-specific stimulation pattern in FES. The musculotendon system was modeled as a torque-generator and all the passive systems of the musculotendon working at the same joint were included in the skeletal model. Through this, it became possible that the whole model to be identified by using the experimental joint torque or the joint angle trajectories. The model parameters were grouped as recruitment of muscle fibers, passive skeletal system, static and dynamic musculotendon systems, which were identified later in sequence. The parameters in each group were successfully estimated and the maximum normalized RMS errors in all the estimation process was 8%. The model predictions with estimated parameter values were in a good agreement with the experimental results for the sinusoidal, triangular and sawlike stimulation, where the normalized RMS error was less than 17%, Above results show that the suggested musculoskeletal model and its parameter estimation method is reliable.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.116-125
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• 2007

Human muscle skeletal model was developed for biomechanical study. The human model was consists with 19 bone-skeleton and 122 muscles. Muscle number of upper limb, trunk and lower limb part are 28, 60, 34 respectively. Bone was modeled with 3D beam element and muscle was modeled with spar element. For upper limb muscle modelling, rectus abdominis, trapezius, deltoideus, biceps brachii, triceps brachii muscle and other main muscles were considered. Lower limb muscle was modeled with gastrocenemius, gluteus maximus, gluteus medius and related muscles. The biomechanical stress and strain analysis of human was conducted by proposed finite element analysis model under Kumdo head hitting motion. In this study structural analysis has been performed in order to investigate the human body impact by Kumdo head hitting motion. As the results, the analytical displacement, stress and strain of human body are presented.

• Korean Journal of Computational Design and Engineering
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• v.17 no.6
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• pp.443-455
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• 2012

The configuration of a musculoskeletal (MS) system is closely related to the individual motions of the human body. Many researches have been focused on evaluating the associations between the MS configuration and the individual motion using patient-specific MS models, but it still remains a challenging issue to accurately predict the motion by differed configurations of the MS system. The main objective of this paper is to predict the changes of a patient-specific gait by altering the geometric parameters of the hip joint using function-based morphing method (FBM). FBM is suitable for motion analysis since this method provide a robust way to morph a MS model while preserving the biomechanical functions of the bones. Computed-muscle control technique is used to calculate the muscle excitations to reproduce the targeted motion within a digital MS model without the motion-captured data. We applied this approach to a patient who has an abnormal gait pattern. Results showed that the femoral neck length and the angle significantly affect to the motion especially for the hip abduction angle during gait, and that this approach is suitable for gait prediction.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.8 s.197
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• pp.130-137
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• 2007

The optimized prosthetic mass distribution was a controversial problem in the previous studies because they are not supported by empirical evidence. The purpose of the present study was to evaluate the effect of prosthetic mass properties by modeling musculoskeletal system, based on the gait analysis data from two above-knee amputees. The joint torque at hip joint was calculated using inverse dynamic analysis as the mass was changed in knee and foot prosthetic components with the same joint kinematics. The results showed that the peak flexion and abduction torque at the hip joint were 5 Nm and 15 Nm when the mass of the knee component was increased, greater than the peak flexion and abduction torque of the control group at the hip joint, respectively. On the other hand, when the mass of the foot component was increased, the peak flexion and abduction torque at the hip joint were 20 Nm and 15 Nm, greater than the peak flexion and abduction torque of the control, respectively. The hip flexion torque was 4.71-fold greater and 7.92-fold greater than the hip abduction torque for the knee mass increase and the foot mass increase on the average, respectively. Therefore, we could conclude that the effect of foot mass increase was more sensitive than that of knee mass increase for the hip flexion torque. On the contrary, the mass properties of the knee and foot components were not sensitive for the hip abduction torque. In addition, optimized prosthetic mass and appropriate mass distributions were needed to promote efficiency of rehabilitation therapy with consideration of musculoskeletal systems of amputees.