Robotic legs mimic human walking gait

Said to be the first successfully to model walking in a biologically accurate manner, the robot features simplified versions of the neural architecture, musculoskeletal architecture and sensory feedback pathways in the human body. A key component of the human walking system is the central pattern generator (CPG). The CPG is a neural 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 that are responding to the environment. This is what allows people to walk without needing to think about it. The simplest form of a CPG is a half-centre, which consists of just two neurons that fire signals alternatively, producing a rhythm. The robot contains an artificial half-centre as well as sensors that deliver information back to the half-centre, including load sensors that sense force in the limb when the leg is pressed against a stepping surface. Dr Theresa Klein, from the University of Arizona, commented: "Interestingly, we were able to produce a walking gait, without balance, which mimicked human walking with only a simple half-centre controlling the hips and a set of reflex responses controlling the lower limb." The researchers hypothesise that babies start off with a simple half-centre, 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 may explain how people with spinal cord injuries can regain walking ability if properly stimulated in the months after the injury," Dr Klein concluded.