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TECHNOLOGUE

These 'Bots Are Made for Walking

Stephen Piazza

Exaggerating Your Faults

As promising as impedance control may be, that kind of therapy presumes that the patient has a nervous system capable of accurately sensing and responding to deviations from correct limb motions. Patients who have difficulty walking because of conditions such as incomplete spinal cord injury or stroke frequently also have sensory deficits that prevent them from making full use of neural feedback from their muscles, tendons, and joints.

Fortunately, there are ways for sensors to provide this missing feedback by translating the changing configuration of a robotic exoskeleton into an animation on a virtual reality (VR) display that the patient views on a video screen. Such electronic sensors can also produce cleaner signals of motion than the noisy biological sensors in our bodies.

In 2009 Anat Mirelman and Judith Deutsch of the University of Medicine and Dentistry of New Jersey and Paolo Bonato of Harvard Medical School put the theory to the test. They found that stroke patients undergoing robotic gait training were able to walk farther and faster when their therapy was enhanced with a VR display. The researchers attributed the improvement partly to VR showing the subjects how their limbs were moving, and partly to the display functioning like a video game that kept patients engaged during training.

 

If patients relearning how to walk benefit from knowing the true positions of their legs, some neuroscientists have reasoned, why stop at telling them the truth? Patients may be able to learn even better and faster through error augmentation, which sounds much better than “lying.” In this scheme, when the patient moves in a manner that deviates from what is desired, an exaggerated depiction of the deviation is presented to him or her on a screen. Like a teacher circling mistakes on a test with a red pen, robotic sensors’ output may be amplified to draw the patient’s attention to movement error and thus motivate stronger and faster corrections.

Curiously, it seems that patients learn more rapidly when their errors are moderately embellished, but there is no benefit in telling big whoppers to the nervous system. James Patton of the University of Illinois at Chicago explains that there seems to be a “sweet spot” for achieving the greatest benefit from amplifying errors. Early trials indicate that there has to be enough magnification to involve more of the nervous system in the learning process, according to Patton, but not so much that the patient begins to doubt that he’s really observing his own behavior.








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