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Researchers from the University of Arizona have produced a robotic set of legs that is believed to be the first to fully model walking in a biologically accurate manner. The biological accuracy of the robot could someday help researchers understand how to help spinal-cord-injury patients recover the ability to walk.

A key component of the system is the central pattern generator (CPG), a neural network in the lumbar region of the spinal cord that generates rhythmic muscle signals. The CPG produces, then controls, these signals by gathering information from different parts of the body that are responding to the environment.

The simplest form of a CPG is a half-center, which consists of just two neurons that fire signals alternatively, producing a rhythm. The robot contains an artificial half-center as well as sensors that deliver information back to the half-center, including load sensors that sense force int he limb when the leg is pressed against a stepping surface.

The researchers hypothesized that babies start off with a simple half-center, similar to the one developed in this robot, and over time, they "learn" a network for a more complex walking pattern. This underlying network may also form the core of the CPG and explain how people with spinal cord injuries can regain walking ability if properly stimulated in the months after the injury, said Dr. Theresa Klein, co-author of the study.

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