@Article{murai:ral:2016,
  author    = {Murai, Akihiko and Endo, Yui and Tada, Mitsunori},
  title     = {Anatomographic volumetric skin-musculoskeletal model and its kinematic deformation with surface-based SSD},
  journal   = {IEEE Robotics and Automation Letters},
  year      = {2016},
  volume    = {1},
  number    = {2},
  pages     = {1103--1109},
  month     = {July},
  doi       = {10.1109/LRA.2016.2524069},
  url       = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7396939},
  keywords  = {Simulation and Animation, biomimetics.},
  abstract  = {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 a muscle activity estimation. In this letter, we develop a volumetric skin-musculoskeletal model based on an 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 surfacebased 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.},
  publisher = {IEEE-INST Electrical Electronics Engineers Inc},
  address   = {445 Hoes Lane, Piscataway, NJ 08855-4141, USA}
}