2012
DOI: 10.1016/j.crme.2012.01.002
|View full text |Cite
|
Sign up to set email alerts
|

Multi-objective optimization to predict muscle tensions in a pinch function using genetic algorithm

Abstract: This work is focused on the determination of the thumb and the index finger muscle tensions in a tip pinch task. A biomechanical model of the musculoskeletal system of the thumb and the index finger is developed. Due to the assumptions made in carrying out the biomechanical model, the formulated force analysis problem is indeterminate leading to an infinite number of solutions. Thus, constrained single and multi-objective optimization methodologies are used in order to explore the muscular redundancy and to pr… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2014
2014
2023
2023

Publication Types

Select...
5
2

Relationship

0
7

Authors

Journals

citations
Cited by 7 publications
(3 citation statements)
references
References 28 publications
0
3
0
Order By: Relevance
“…Finite Rigid Elements Method is usually utilized to model the continuum structures [34]. By discretizing the actuator into a series of n links with nonlinear torsional springs in the joints, and using the Denavit-Hartenberg method, a model for the elements' position could be derived in the static situation.…”
Section: Nonlinear Finite Rigid Elements Methods For Free Motion and ...mentioning
confidence: 99%
“…Finite Rigid Elements Method is usually utilized to model the continuum structures [34]. By discretizing the actuator into a series of n links with nonlinear torsional springs in the joints, and using the Denavit-Hartenberg method, a model for the elements' position could be derived in the static situation.…”
Section: Nonlinear Finite Rigid Elements Methods For Free Motion and ...mentioning
confidence: 99%
“…21 From this perspective, it is well accepted that the human movements result from a compromise between the loading of both muscular and joint structures that are in interaction. 14,16,22,23 Still, multi-objective optimisation has been very rarely applied to musculoskeletal modelling, 24 while some inverse identifications of the objective functions have been proposed. 25,26 Nevertheless, in these studies, the concurrent objective functions have remained the sum of musculo-tendon forces, stresses, or activations at different powers.…”
Section: Introductionmentioning
confidence: 99%
“…It can be used to handle the complicated and non-linear problems which are difficult to be solved by traditional search methods in particular and it can also be widely applied in such fields as combinatorial optimization, machine learning, self-adaptive control, planning and design as well as artificial life. As a global optimization search algorithm, genetic algorithm is one of the core intelligent computation technologies in the 21st century for it is easy and universal to apply, it has strong robustness, it can be used in parallel processing and it has a wide application scope [8].…”
Section: Genetic Algorithmmentioning
confidence: 99%