Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing in the Elephant Trunk

2024

Miscellaneous

hi

Skin is a complex biological composite consisting of layers with distinct mechanical properties, morphologies, and mechanosensory capabilities. This work seeks to expand the comparative biomechanics field to comparative haptics, analyzing elephant trunk touch by redesigning a previously published human finger-pad model with morphological parameters measured from an elephant trunk. The dorsal surface of the elephant trunk has a thick, wrinkled epidermis covered with whiskers at the distal tip and deep folds at the proximal base. We hypothesize that this thick dorsal skin protects the trunk from mechanical damage but significantly dulls its tactile sensing ability. To facilitate safe and dexterous motion, the distributed dorsal whiskers might serve as pre-touch antennae, transmitting an amplified version of impending contact to the mechanoreceptors beneath the elephant's armor. We tested these hypotheses by simulating soft tissue deformation through high-fidelity finite element analyses involving representative skin layers and whiskers, modeled based on frozen African elephant trunk (Loxodonta africana) morphology. For a typical contact force, quintupling the stratum corneum thickness to match dorsal trunk skin reduces the von Mises stress communicated to the dermis by 18%. However, adding a whisker offsets this dulled sensing, as hypothesized, amplifying the stress by more than 15 at the same location. We hope this work will motivate further investigations of mammalian touch using approaches and models from the ample literature on human touch.

@misc{Schulz24-SICBA-Skin,
  title = {Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing in the Elephant Trunk},
  author = {Schulz, Andrew and Serhat, Gokhan and Kuchenbecker, Katherine J.},
  howpublished = {Abstract presented at the Society for Integrative and Comparative Biology Annual Meeting (SICB)},
  address = {Seattle, USA},
  month = jan,
  year = {2024},
  doi = {},
  month_numeric = {1}
}