Modelo músculo-esquelético del miembro inferior: Un enfoque teórico en busca de la aplicabilidad clínica

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Fecha
11/2013
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Sociedad Argentina de Bioingeniería
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Argentina de Bioingeniería
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0329-5257
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Español
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Resumen
El análisis biomecánico, es una herramienta habitual de análisis clínico en sujetos con alteraciones motrices. Sin embargo, la distribución de las fuerzas musculares individuales durante el ciclo de marcha no está completamente representada. Un modelo músculo-esquelético representa mediante un conjunto de parámetros numéricos la interacción del sistema óseo-artro-múscular aportando estrategias más efectivas en el análisis y posterior abordaje terapéutico. El sistema locomotor humano es redundante y utiliza óptimos criterios de selección muscular para desarrollar un movimiento. Esto lleva a la utilización de métodos matemáticos de optimización que utilizan principios fisiológicos para explicar el mecanismo y significado funcional de las fuerzas musculares. En este trabajo se desarrolló un modelo musculo-esquelético del miembro inferior en el plano sagital constituido por once músculos y se lo analizó sobre cinco sujetos sin alteraciones de la marcha. El tejido muscular es representado mediante la utilización de un modelo de Hill. Para la resolución del problema de optimización se utilizó el algoritmo SQP. Se compararon los resultados obtenidos con modelos ya existentes. Se logró reflejar los lineamientos a seguir en el desarrollo de un modelo aplicable al ambiente clínico, ayudando a predecir el comportamiento funcional de los músculos y sus posibles modificaciones ante una patología.
Biomechanical analysis is a common tool in clinician settings for the analysis of subjects with motor abnormalities. However, the individual muscle forces behavior through of the gait cycle is not fully represented on the gait analysis. Musculoskeletal models represent a set of numerical parameters showing the interaction of the system bone-joint-muscles, providing more effective strategies in the analysis and subsequent therapeutic approach. The human musculoskeletal system is redundant and uses optimal selection criteria for developing a muscular movement. This leads to the use of mathematical optimization methods that utilize physiological mechanism to explain the principles and functional significance of muscle forces.A musculoskeletal model of the lower limb was developed in this paper. The model represents the sagittal plane of movement and it consists of eleven muscles.In this work were analyzed five subjects without abnormal gait. Muscle tissue was represented by a Hill-Type model. To solve the static optimization problem the SQP algorithm was used. Our estimationsof the muscles force were compared with other musculoskeletal model, developed by other researcher groups. Through this work was possible to reflect the guidelines to follow in the developing a musculoskeletal model applicable in the clinical setting, helping to predict the functional behavior of muscles and the possible modifications from a pathological gait.
Biomechanical analysis is a common tool in clinician settings for the analysis of subjects with motor abnormalities. However, the individual muscle forces behavior through of the gait cycle is not fully represented on the gait analysis. Musculoskeletal models represent a set of numerical parameters showing the interaction of the system bone-joint-muscles, providing more effective strategies in the analysis and subsequent therapeutic approach. The human musculoskeletal system is redundant and uses optimal selection criteria for developing a muscular movement. This leads to the use of mathematical optimization methods that utilize physiological mechanism to explain the principles and functional significance of muscle forces.A musculoskeletal model of the lower limb was developed in this paper. The model represents the sagittal plane of movement and it consists of eleven muscles.In this work were analyzed five subjects without abnormal gait. Muscle tissue was represented by a Hill-Type model. To solve the static optimization problem the SQP algorithm was used. Our estimationsof the muscles force were compared with other musculoskeletal model, developed by other researcher groups. Through this work was possible to reflect the guidelines to follow in the developing a musculoskeletal model applicable in the clinical setting, helping to predict the functional behavior of muscles and the possible modifications from a pathological gait.
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