Human bipedal instability in tree canopy environments is reduced by "light touch" fingertip support.

Whether tree canopy habitats played a sustained role in the ecology of ancestral bipedal hominins is unresolved. Some argue that arboreal bipedalism was prohibitively risky for hominins whose increasingly modern anatomy prevented them from gripping branches with their feet. Balancing on two legs is indeed challenging for humans under optimal conditions let alone in forest canopy, which is physically and visually highly dynamic. Here we quantify the impact of forest canopy characteristics on postural stability in humans. Viewing a movie of swaying branches while standing on a branch-like bouncy springboard destabilised the participants as much as wearing a blindfold. However "light touch", a sensorimotor strategy based on light fingertip support, significantly enhanced their balance and lowered their thigh muscle activity by up to 30%. This demonstrates how a light touch strategy could have been central to our ancestor's ability to avoid falls and reduce the mechanical and metabolic cost of arboreal feeding and movement. Our results may also indicate that some adaptations in the hand that facilitated continued access to forest canopy may have complemented, rather than opposed, adaptations that facilitated precise manipulation and tool use.

An efficient approach to converting three-dimensional image data into highly accurate computational models.

Image-based meshing is opening up exciting new possibilities for the application of computational continuum mechanics methods (finite-element and computational fluid dynamics) to a wide range of biomechanical and biomedical problems that were previously intractable owing to the difficulty in obtaining suitably realistic models. Innovative surface and volume mesh generation techniques have recently been developed, which convert three-dimensional imaging data, as obtained from magnetic resonance imaging, computed tomography, micro-CT and ultrasound, for example, directly into meshes suitable for use in physics-based simulations. These techniques have several key advantages, including the ability to robustly generate meshes for topologies of arbitrary complexity (such as bioscaffolds or composite micro-architectures) and with any number of constituent materials (multi-part modelling), providing meshes in which the geometric accuracy of mesh domains is only dependent on the image accuracy (image-based accuracy) and the ability for certain problems to model material inhomogeneity by assigning the properties based on image signal strength. Commonly used mesh generation techniques will be compared with the proposed enhanced volumetric marching cubes (EVoMaCs) approach and some issues specific to simulations based on three-dimensional image data will be discussed. A number of case studies will be presented to illustrate how these techniques can be used effectively across a wide range of problems from characterization of micro-scaffolds through to head impact modelling.