Conventional musculoskeletal models mainly consist of bones modeled by rigid linkages, and muscles, tendons, and ligaments modeled by ideal wires. The lack of volumetric modeling of muscle makes a representation of interaction between muscles and natural muscle pathway difficult. This difficulty results in a physiologically inappropriate estimation of a muscle momentum arm that is critical for muscle activity estimation. In this project propose, a volumetric skin-musculoskeletal model based on anatomographic human shape database to improve an estimation of a muscle momentum arm. A volumetric deformation of surface skin and muscle is realized by an extended skeleton subspace deformation (SSD, the linear blend skinning algorithm) that considers a surface profile of bone with low computational cost. This extended SSD considers a sub-bone that is projected to the bone surface polygon so that the skin and muscle deformation is significantly affected by the bone surface profile. The surface based SSD realized the natural skin deformation avoiding a penetration between skin and bones during trunk rotation that results in a physiologically appropriate estimation of a muscle momentum arm. The volumetric skin-musculoskeletal model and the surface based SSD estimates the momentum arm of vastus lateralis with 14.1% maximum error from a literature values, though there is 44.8% maximum error with the wire musculoskeletal model. This model would accurize a muscle activity estimation that leads to a more correct understanding of human motion control/generation mechanisms. This project is implemented with MATLAB software.


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