When your brain’s neural pathways are impaired through injury, age, or illness, muscles are deprived of the sensory information they need to perform the constant balancing act required for normal movement and standing. In a project designed to build robots that can balance like humans, researchers at Georgia Tech and Emory University have created a computer simulation that sheds new light on how the nervous system reinvents its communication with muscles after sensory loss. The project could help better diagnose and rehabilitate patients with balance problems by retraining their muscles.

In most people, the nervous system collects sensory information from the body (skin, ears, feet, arms, eyes) and transmits it to the muscles that control balance. When that information changes through the introduction of something like a strong wind, a raised crack in the pavement, or an accidental bump from a nearby stranger, the nervous system sends the new information to the muscles and they adjust accordingly to maintain balance. For those who suffer injuries to the nervous system or senses that report to the nervous system, it can lead to balance problems.

ImageThe researchers interpret how commands from the nervous system to muscles (measured through electrical signals in the muscles) are changed by sensory impairment, and how these changes affect balance control. The team hypothesized that the nervous system relies on the relationship between the body’s center of gravity and its environment to control balance. They found that the best predictor of how muscles would be activated when the subject experienced a balance threat was not the motion of the individual body parts, but the horizontal motion of the body’s center of gravity.

The researchers created a computer simulation that could accurately simulate standing balance and muscle reactions to balance disturbances by focusing on the relation of the subject’s center of gravity to the ground.

The team determined that subjects who had impaired sensory information were slowly using new sensory pathways to track the motion of the body’s center of gravity, compensating for the loss of information from the damaged sensory pathways. In effect, the subjects’ muscles were using different neural information to perform the same balance tasks.

The research team is testing its simulation with human subjects and a small robot with simulated muscles. When applied to a robot, these neural communication patterns allowed the robot to successfully move fluidly like an animal, in contrast to what its gears and motors might suggest.

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