Caracterización de tejido cerebral artificial utilizando Inverse-FEM para simular indentación y comprensión

Autores/as

  • Elizabeth Mesa-Múnera Investigador Universidad Nacional de Colombia, Medellín–Colombia.
  • Juan F Ramírez–Salazar Investigador Universidad Nacional de Colombia, Medellín–Colombia.
  • Pierre Boulanger University of Alberta
  • John W Branch Researcher Universidad Nacional de Colombia, Medellín–Colombia. https://orcid.org/0000-0002-0378-028X (no autenticado)

DOI:

https://doi.org/10.17230/ingciencia.8.16.1

Palabras clave:

inverse-FEM, Ensayo a Compresión, Indentación, Calibración de tejidos, Simuladores Quirúrgicos.

Resumen

Una simulación realista de la interacción tejido-herramienta es necesaria para desarrollar simuldores quirúrgicos, y la presición en modelos biomecánicos de tejidos es determinante para cumplir tal fin. Los trabajos previos han caracterizado las propiedades de tejidos blandos; sin embargo, ha faltado una validación apropiada de los resultados. En este trabajo se determinaron las propiedades mecánicas de un tejido blando minimizando la diferencia entre las mediciones experimentales y la solución analítica o simulada del problema. Luego, fueron seleccionados los parámetros que mejor se ajustaron a los datos experimentales para simular una compresión con fricción y la indentación de una aguja con punta plana. Se concluye que el inverse-FEM permite la precisa estimación de las propiedades del material. Además, estos resultados fueron validados con varias interacciones tejido-herramienta sobre el mismo espécimen.

MSC: 74S05

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Biografía del autor/a

  • Elizabeth Mesa-Múnera, Investigador Universidad Nacional de Colombia, Medellín–Colombia.

    Mechanical Engineer, M.Sc in Systems Engineering,

  • Juan F Ramírez–Salazar, Investigador Universidad Nacional de Colombia, Medellín–Colombia.

    Mechanical Engineer, M.Sc in Systems Engineering,

  • Pierre Boulanger, University of Alberta
    Ph.D in Electrical Engineering
  • John W Branch, Researcher Universidad Nacional de Colombia, Medellín–Colombia.

    Ph.D in Systems Engineering

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Publicado

2012-11-30

Número

Sección

Artículos

Cómo citar

Mesa-Múnera, E., Ramírez–Salazar, J. F., Boulanger, P., & Branch, J. W. (2012). Caracterización de tejido cerebral artificial utilizando Inverse-FEM para simular indentación y comprensión. Ingeniería y Ciencia, 8(16), 11-36. https://doi.org/10.17230/ingciencia.8.16.1

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