In Vivo Measurement of Thumb Joint Reaction Forces During Smartphone Manipulation: A Biomechanical Analysis

2019 ◽  
Vol 37 (11) ◽  
pp. 2437-2444 ◽  
Author(s):  
Wanlim Kim ◽  
Yusung Kim ◽  
Hyung‐Soon Park
Keyword(s):  
Biomechanical Analysis ◽  
In Vivo Measurement ◽  
Joint Reaction Forces ◽  
Reaction Forces ◽  
Joint Reaction

Comparison of Three-Dimensional Patellofemoral Joint Reaction Forces in Persons With and Without Patellofemoral Pain

2014 ◽  
Vol 30 (4) ◽  
pp. 493-500 ◽  
Author(s):  
Yu-Jen Chen ◽  
Christopher M. Powers
Keyword(s):  
Patellofemoral Joint ◽  
Three Dimensional ◽  
Patellofemoral Pain ◽  
Biomechanical Analysis ◽  
Control Group ◽  
Three Dimensional Model ◽  
Joint Reaction Forces ◽  
Reaction Forces ◽  
Magnetic Resonance Imaging Mri ◽  
Joint Reaction

The purpose of this study was to determine if persons with patellofemoral pain (PFP) exhibit differences in patellofemoral joint reaction forces (PFJRFs) during functional activities. Forty females (20 PFP, 20 controls) underwent two phases of data collection: (1) magnetic resonance imaging (MRI) and (2) biomechanical analysis during walking, running, stair ascent, and stair descent. A previously described three-dimensional model was used to estimate PFJRFs. Resultant PFJRFs and the orthogonal components were reported. The PFP group demonstrated lower peak resultant PFJRFs and posterior component and superior component of the PFJRFs compared with the control group across all conditions. However, the PFP group had a higher peak lateral component of the PFJRF in three out of the four conditions evaluated. The lower resultant PFJRFs suggested that individuals with PFP may employ strategies to minimize patellofemoral joint loading, but it did not result in diminished lateral forces acting on the patella.

Influence of the Musculotendon Dynamics on the Muscle Force-Sharing Problem of the Shoulder—A Fully Inverse Dynamics Approach

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Quental Carlos ◽  
Azevedo Margarida ◽  
Ambrósio Jorge ◽  
Gonçalves S. B. ◽  
Folgado João
Keyword(s):  
Muscle Activation ◽  
Inverse Dynamics ◽  
Glenohumeral Joint ◽  
Inverse Dynamic ◽  
Force Sharing ◽  
Joint Reaction Forces ◽  
Reaction Forces ◽  
Muscle Activations ◽  
Joint Reaction

Abstract Most dynamic simulations are based on inverse dynamics, being the time-dependent physiological nature of the muscle properties rarely considered due to numerical challenges. Since the influence of muscle physiology on the consistency of inverse dynamics simulations remains unclear, the purpose of the present study is to evaluate the computational efficiency and biological validity of four musculotendon models that differ in the simulation of the muscle activation and contraction dynamics. Inverse dynamic analyses are performed using a spatial musculoskeletal model of the upper limb. The muscle force-sharing problem is solved for five repetitions of unloaded and loaded motions of shoulder abduction and shoulder flexion. The performance of the musculotendon models is evaluated by comparing muscle activation predictions with electromyography (EMG) signals, measured synchronously with motion for 11 muscles, and the glenohumeral joint reaction forces estimated numerically with those measured in vivo. The results show similar muscle activations for all muscle models. Overall, high cross-correlations are computed between muscle activations and the EMG signals measured for all movements analyzed, which provides confidence in the results. The glenohumeral joint reaction forces estimated compare well with those measured in vivo, but the influence of the muscle dynamics is found to be negligible. In conclusion, for slow-speed, standard movements of the upper limb, as those studied here, the activation and musculotendon contraction dynamics can be neglected in inverse dynamic analyses without compromising the prediction of muscle and joint reaction forces.

scholarly journals Determination of biological joint reaction forces from in-vivo experiments using a hybrid combination of biomechanical and mechanical engineering software

2020 ◽  
Vol 21 (6) ◽  
pp. 623
Author(s):  
Joanne Becker ◽  
Emmanuel Mermoz ◽  
Jean-Marc Linares
Keyword(s):  
Mechanical Engineering ◽  
Bone Geometry ◽  
Simulation Software ◽  
Ground Reaction Forces ◽  
Mechanical Modeling ◽  
In Vivo Experiments ◽  
Joint Reaction Forces ◽  
Reaction Forces ◽  
Joint Reaction

In biomechanical field, several studies used OpenSim software to compute the joint reaction forces from kinematics and ground reaction forces measurements. The bio-inspired joints design and their manufacturing need the usage of mechanical modeling and simulation software tools. This paper proposes a new hybrid methodology to determine biological joint reaction forces from in vivo measurements using both biomechanical and mechanical engineering softwares. The methodology has been applied to the horse forelimb joints. The computed joint reaction forces results would be compared to the results obtained with OpenSim in a previous study. This new hybrid model used a combination of measurements (bone geometry, kinematics, ground reaction forces…) and also OpenSim results (muscular and ligament forces). The comparison between the two models showed values with an average difference of 8% at trotting and 16% at jumping. These differences can be associated with the differences between the modelling strategies. Despite these differences, the mechanical modeling method allows the computation of advanced simulations to handle contact conditions in joints. In future, the proposed mechanical engineering methodology could open the door to define a biological digital twin of a quadruped limb including the real geometry modelling of the joint.

How Well Does a Musculoskeletal Model Predict GH-Joint Contact Forces? Comparison With In-Vivo Data

2009 ◽  
Author(s):  
A. Asadi Nikooyan ◽  
H. E. J. Veeger ◽  
P. Westerhoff ◽  
F. Graichen ◽  
G. Bergmann ◽  
...  
Keyword(s):  
Large Scale ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Motion Data ◽  
Joint Reaction Forces ◽  
Joint Contact ◽  
Reaction Forces ◽  
Quantitative Validation ◽  
Joint Reaction

The Delft Shoulder and Elbow Model (DSEM), a large-scale musculoskeletal model, allows for estimation of individual muscle and joint reaction forces in the shoulder and elbow complex. Although the model has been qualitatively verified previously using EMG signals, quantitative validation has not yet been feasible. In this paper we report on the validation of the DSEM by comparing the GH-joint contact forces estimated by the DSEM with the in-vivo forces measured by a recently developed instrumented shoulder endoprosthesis, capable of measuring the glenohumeral (GH) joint contact forces in-vivo [1]. To validate the model, two patients with instrumented shoulder hemi-arthroplasty were measured. The measurement process included the collection of motion data as well as in-vivo joint reaction forces. Segment and joint angles were used as the model inputs to estimate the GH-joint contact forces. The estimated and recorded GH-joint contact forces for Range of Motion (RoM) and force tasks were compared based on the magnitude of the resultant forces. The results show that the estimated force follows the measured force for abduction and anteflexion motions up to 80 and 50 degrees arm elevations, respectively, while they show different behaviors for angles above 90 degrees (decrease is estimated but increase is measured). The DSEM underestimates the peak force for RoM (up to 38% for abduction motion and 64% for anteflexion motion), while overestimates the peak forces (up to 90%) for most directions of performing the force tasks.

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