Une approche heuristique appliquée en biomécanique

Toshev, Y.; Monchaud, S.

doi:10.1016/s1251-8069(97)86828-5

Cited by 1 publication

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“…On the other hand, numerical optimization techniques based on heuristic methods and the Pareto optimality concept have been often used in the fields of biomechanics, engineering and science [12][13][14]. Multi-objective optimization based on genetic algorithm is also used in several works [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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

Bensghaier

Romdhane

Benouezdou

2012

Comptes Rendus. Mécanique

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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 predict optimal muscle tension distributions. Various models are investigated using the optimization process. The basic criteria to minimize are the sum of the muscle stresses, the sum of individual muscle tensions and the maximum muscle stress. The multi-objective optimization is solved using a Pareto genetic algorithm to obtain non-dominated solutions, defined as the set of optimal distributions of muscle tensions. The results show the advantage of the multi-objective formulation over the single objective one. The obtained solutions are compared to those available in the literature demonstrating the effectiveness of our approach in the analysis of the fingers musculoskeletal systems when predicting muscle tensions.

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