Study on biomechanical simulation of knee joint during gait cycle by using inverse dynamic analysis

2017 ◽  
Vol 2017.55 (0) ◽  
pp. K0102
Author(s):  
Yuta YAMAMOTO ◽  
Xian CHEN ◽  
Junji OHGI ◽  
Fei JIANG
Keyword(s):  
Knee Joint ◽  
Dynamic Analysis ◽  
Gait Cycle ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis ◽  
Biomechanical Simulation

scholarly journals Changes in hip Joint Contact Stress During a Gait Cycle based on the Individualized Modeling Framework of"Gait-Musculoskeletal System-Finite Element"

2021 ◽  
Author(s):  
Binglang Xiong ◽  
Peng Yang ◽  
Tianye Lin ◽  
Jinli Xu ◽  
Yong Xie ◽  
...  
Keyword(s):  
Finite Element ◽  
Dynamic Analysis ◽  
Hip Joint ◽  
Contact Stress ◽  
Stance Phase ◽  
Gait Cycle ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis ◽  
Subject Specific ◽  
Maximum Contact

Abstract Objective: To construct a comprehensive simulation framework of "gait-musculoskeletal system(MS)-finite element(FE)" for analysis of hip joint dynamics characteristics and the changes in the contact stress in the hip throughout a gait cycle.Methods:Two healthy volunteers (male and female) were recruited. The 3D gait trajectories during normal walking and the CT images including the hip and femur of the volunteers were obtained. CT Imaging data in the DICOM were extracted for subjected 3D hip joint reconstruction. The reconstructed 3D model files were used to realize the subject-specific registration of the pelvis and thigh segment of general musculoskeletal model. The captured marker trajectory data were used to drive subject-specific musculoskeletal model to complete inverse dynamic analysis. Results of inverse dynamic analysis were exported and appliedas boundary and load settings of the hip joint finite element in ABAQUS. Finally, the finite element analysis(FEA) was performed to analyze contact stress of hip joint during a gait cycle of left foot.Results: In the inverse dynamic analysis, the dynamic changes of the main hip-femoral muscle force with respect to each phase of a single gait cycle were plotted. The hip joint reaction force reached a maximum value of 2.9%BW（Body weight）and appeared at the end of the terminal stance phase. Twin peaks appeared at the initial contact phase and the end of the terminal stance phase respectively. FEA showed the temporal changes in contact stress in the acetabulum. In the visual stress cloud chart, the acetabular contact stress was mainly distributed in the dome of the acetabulum and in the anterolateral area at the top of the femoral head during a single gait cycle. The acetabular contact area was 293.8-998.4 mm2 and the maximum contact area appear at the mid-stance phase or the loading response phase of gait. The maximum contact stress of the acetabulum reached 6.91 Mpa (Model 1) / 6.92 Mpa(Model 2) at the terminal stance phase. Conclusions:The "Gait-MS-FE" technology is integrated to construct a comprehensive simulation framework. Based on human gait trajectories and their CT images, individualized simulation modeling can be achieved. Subject-specific gait in combination with an inverse dynamic analysis of the MS provides pre-processing parameters for FE simulation for more accurate biomechanical analysis of hip joint.

Experimental Validation of a Dynamic Simulation

1990 ◽  
Author(s):  
K. Harold Yae ◽  
Su-Tai Chern ◽  
Howyoung Hwang
Keyword(s):  
Dynamic Analysis ◽  
Dynamic Simulation ◽  
Time Domain ◽  
Experimental Validation ◽  
Initial Conditions ◽  
Hydraulic Cylinder ◽  
Force Output ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis ◽  
The Time Domain

Abstract Using forward and inverse dynamic analysis, the dynamic simulation of a backhoe has been compared with experiments. In the experiment, recorded were the configuration and force histories; that is, velocity and position, and force output from the hydraulic cylinder-all were measured in the time domain. When the experimental force history is used as driving force in the simulation, forward dynamic analysis produces a corresponding motion history. And when the experimental motion history is used as if a prescribed trajectory, inverse dynamic analysis generates a corresponding force history. Therefore, these two sets of motion and force histories — one set from experiment, and the other from the simulation that is driven forward and backward with the experimental data — are compared in the time domain. The comparisons are discussed in regard to the effects of variations in initial conditions, friction, and viscous damping.

Kinetic and Dynamic Modeling of Single ActuatorWave-Like Robot

Robotica ◽  
2019 ◽  
Vol 37 (11) ◽  
pp. 1971-1986
Author(s):  
Ruoyu Feng ◽  
Peng Zhang ◽  
Junfeng Li ◽  
Hexi Baoyin
Keyword(s):  
Power Consumption ◽  
Dynamic Analysis ◽  
Dynamic Modeling ◽  
Dynamic Equation ◽  
Kinematic Model ◽  
Theoretical Models ◽  
Equation Of Motion ◽  
Kinematics And Dynamics ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis

SummaryIn this study, the kinematics and dynamics of a single actuator wave (SAW)-like robot are explored. Comprising a helical spine and links, SAW has the potential for miniaturization. A kinematic model for SAW is firstly established, and the dynamic equation of motion is derived based on Kane’s method. For validation, the motion of SAW is simulated using both MATLAB and ADAMS, and the comparison of results demonstrates the effectiveness of the theoretical models. Then the inverse dynamic analysis is performed to reveal the power consumption. Finally, robot prototypes are developed and tested to confirm the robot velocity predicted by simulations.

Inverse Dynamic Analysis and Linearisation of a High Speed Parallel Mechanism

2005 ◽  
Author(s):  
M. Necip Sahinkaya ◽  
Yanzhi Li
Keyword(s):  
Dynamic Analysis ◽  
Parallel Mechanism ◽  
High Speed ◽  
Inverse Dynamics ◽  
Motion Path ◽  
Model Parameters ◽  
Control Input ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis ◽  
Dynamics Models

Inverse dynamic analysis of a three degree of freedom parallel mechanism driven by three electrical motors is carried out to study the effect of motion speed on the system dynamics and control input requirements. Availability of inverse dynamics models offer many advantages, but controllers based on real-time inverse dynamic simulations are not practical for many applications due to computational limitations. An off-line linearisation of system and error dynamics based on the inverse dynamic analysis is developed. It is shown that accurate linear models can be obtained even at high motion speeds eliminating the need to use computationally intensive inverse dynamics models. A point-to-point motion path for the mechanism platform is formulated by using a third order exponential function. It is shown that the linearised model parameters vary significantly at high motion speeds, hence it is necessary to use adaptive controllers for high performance.

scholarly journals Control of the boundary conditions of a dynamic knee simulator

2015 ◽  
Vol 6 (2) ◽  
pp. 7 ◽  
Author(s):  
Jan Tiré ◽  
Jan Victor ◽  
Patrick De Baets ◽  
Matthias Verstraete
Keyword(s):  
Boundary Conditions ◽  
Dynamic Analysis ◽  
Ankle Joint ◽  
Hip Joint ◽  
Degrees Of Freedom ◽  
Muscle Forces ◽  
Inverse Dynamic ◽  
Human Knee ◽  
Inverse Dynamic Analysis ◽  
Knee Simulator

At Ghent University a dynamic knee simulator to analyse the kinematics of a human knee has been developed. The rig is designed to perform tests on a mechanical hinge or on a human knee (with or without a prosthesis). The rig has one degree of freedom in a hip joint and four degrees of freedom in an ankle joint. There is currently one actuator that simulates the quadriceps forces. Two additional actuators are proposed in this paper to simulate the hamstrings forces. The magnitude and phase of the forces varies significantly during the movement (e.g. cycling or squatting). Literature indicates that the maximum muscle forces do not exceed 2000 N. An inverse dynamic analysis, using the musculoskeletal software AnyBody, is proposed to determine the evolution of these forces during the studied movements.

Interlimb Transfer of Novel Inertial Dynamics Is Asymmetrical

2004 ◽  
Vol 92 (1) ◽  
pp. 349-360 ◽  
Author(s):  
Jinsung Wang ◽  
Robert L. Sainburg
Keyword(s):  
Dynamic Analysis ◽  
Initial Training ◽  
Flexor Muscle ◽  
Inverse Dynamic ◽  
Subsequent Performance ◽  
Inverse Dynamic Analysis ◽  
Dynamic Strategy ◽  
Direction Control ◽  
Muscle Torques ◽  
Interaction Torques

Mechanisms underlying interlimb transfer of adaptation to visuomotor rotations have recently been explored in depth. However, little data are available regarding interlimb transfer of adaptation to novel inertial dynamics. The present study thus investigated interlimb transfer of dynamics by examining the effect of initial training with one arm on subsequent performance with the other in adaptation to a 1.5-kg mass attached eccentrically to the forearm. Using inverse dynamic analysis, we examined the changes in torque strategies associated with adaptation to the extra mass, and with interlimb transfer of that adaptation. Following initial training with the dominant arm, nondominant arm performance improved substantially in terms of linearity and initial direction control as compared with naïve performance. However, initial training with the nondominant arm had no effect on subsequent performance with the dominant arm. Inverse dynamic analysis revealed that improvements in kinematics were implemented by increasing flexor muscle torques at the elbow to counter load-induced increases in extensor interaction torques as well as increasing flexor muscle torques at the shoulder to counter the extensor actions of elbow muscle torque. Following opposite arm adaptation, the nondominant arm adopted this dynamic strategy early in adaptation. These findings suggest that dominant arm adaptation to novel inertial dynamics leads to information that can be accessed and utilized by the opposite arm controller, but not vice versa. When compared with our previous findings on interlimb transfer of visuomotor rotations, our current findings suggest that adaptations to visuomotor and dynamic transformations are mediated by distinct neural mechanisms.

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