Researchers have developed new software that allows people using robotic prosthetics or external skeletons to walk more safely, more naturally on different terrain types.
The new framework incorporates computer vision into prosthetic leg control and includes powerful artificial intelligence (AI) algorithms that allow the software to better explain uncertainty. Among types of terrains that need adjustment, researchers focused on six robotic prosthetic’s behavior: tile, brick, concrete, grass, “upstairs” and “downstairs”.
This new “environment context” framework combines both software and hardware elements. The researchers designed this framework for use with many different lower-limb robotic exoskeletons or robotic prosthetic devices, but with a twist, they added cameras. The camera is worn on eyeglasses and another camera mounted on the lower-limb prosthesis. They evaluated how AI could use computer vision data from both types of cameras when they are used together or used separately.
"Incorporating computer vision into control software for wearable robotics is an exciting new area of research," says Helen Huang, a co-author of the paper. "We found that using both cameras worked well, but required a great deal of computing power and may be cost-prohibitive. However, we also found that using only the camera mounted on the lower limb worked pretty well - particularly for near-term predictions, such as what the terrain would be like for the next step or two." Huang is the Jackson Family Distinguished Professor of Biomedical Engineering in the Joint Department of Biomedical Engineering at NC State and the University of North Carolina at Chapel Hill.
In order to train the AI system, researchers connected the cameras to able-bodied individuals - that then experienced in many indoor and outdoor environments. Then, they did a proof-of-concept evaluation by having a person with lower-limb amputation wear the cameras while walking through the same environments.
Source: Science Daily
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