US experts have developed what they say are the most biologically-accurate robotic legs yet. Writing in the Journal of Neural Engineering, they said the work could help understanding of how babies learn to walk - and spinal-injury treatment. They created a version of the message system that generates the rhythmic muscle signals that control walking.
The team, from the University of Arizona, were able to replicate the central pattern generator (CPG) - a nerve cell (neuronal) network in the lumbar region of the spinal cord that generates rhythmic muscle signals.
The CPG produces, and then controls, these signals by gathering information from different parts of the body involved in walking, responding to the environment.
This is what allows people to walk without thinking about it.
"Previous robotic models have mimicked human movement: this one goes further and mimics the underlying human control mechanisms driving that movement.
"It may offer a new approach to investigate and understand the link between nervous system control problems and walking pathologies."
Source: Theresa J Klein and M Anthony Lewis. A physical model of sensorimotor interactions during locomotion. 2012 J. Neural Eng. 9 046011. doi:10.1088/1741-2560/9/4/046011
tags: biology, medicine, control, tool,3x3