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- W2893171461 abstract "Due to the limitations of currently available artificial spinal discs stemming from anatomical unfit and unnatural motion, patient-specific elastomeric artificial spinal discs are conceived as a promising solution to improve clinical results. Multimaterial Additive Manufacturing (AM) has the potential to facilitate the production of an elastomeric composite artificial disc with complex personalized geometry and controlled material distribution. Motivated by the potential combined advantages of personalized artificial spinal discs and multi-material AM, a biomimetic multi-material elastomeric artificial disc design with several matrix sections and a crisscross fiber network is proposed in this study. To determine the optimized material distribution of each component for natural motion restoration, a computational method is proposed. The method consists of automatic generation of a patient-specific disc Finite Element (FE) model followed by material property optimization. Biologically inspired heuristics are incorporated into the optimization process to reduce the number of design variables in order to facilitate convergence. The general applicability of the method is verified by designing both lumbar and cervical artificial discs with varying geometries, natural rotational motion ranges, and rotational stiffness requirements. The results show that the proposed method is capable of producing a patient-specific artificial spinal disc design with customized geometry and optimized material distribution to achieve natural spinal rotational motions. Future work focuses on extending the method to also include implant strength and shock absorption behavior into the optimization as well as identifying a suitable AM process for manufacturing." @default.
- W2893171461 created "2018-10-05" @default.
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- W2893171461 date "2018-08-26" @default.
- W2893171461 modified "2023-09-28" @default.
- W2893171461 title "Computational Design of a Personalized Artificial Spinal Disc for Additive Manufacturing With Physiological Rotational Motions" @default.
- W2893171461 doi "https://doi.org/10.1115/detc2018-85921" @default.
- W2893171461 hasPublicationYear "2018" @default.
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