https://www.eurekalert.org/pub_releases/2017-07/aaft-apr071717.php
Credit: Mignardot et al., Science Translational Medicine (2017)
Scientists have developed an algorithm for a robot-assistive
rehabilitation approach that helps people learn to walk again after
neurological injuries. Their method is now under investigation in a
clinical trial, and may offer better outcomes for patients undergoing
rehabilitation. Rehabilitation programs for spinal cord injuries or
strokes usually involves many hours of supported walking on treadmills
at steady pre-defined paces, but everyday life requires individuals to
move around in all directions and vary their gaits. Seeking an
alternative to current support systems for the upper torso that merely
act as rigid upward props, Jean-Baptiste Mignardot and colleagues used a
robotic harness that helped resist the downward force of gravity while
also allowing subjects to walk forwards, backwards, and side-to-side,
coupled with an algorithm that provided personalized support to address
patient-specific motor defects. The system was controlled by an
artificial neural network that varied the amount of upward and forward
force through a cable harness based on information about 120 different
variables related to body movement. Wearing the harness allowed 26
participants recovering from spinal cord injuries or strokes to walk
with motor abilities comparable to healthy individuals. What's more, one
hour of overground training with the harness and algorithm led to
significant improvements in unsupported walking ability for five
patients with spinal cord injury, whereas the same amount of time on a
treadmill actually impaired locomotion in one subject. The authors say
their results establish a practical framework to apply these concepts in
clinical routines.video at link.
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