While it can be relatively easy for a person with lower limb amputation to walk on flat ground using a basic prosthetic leg, walking up stairs or across uneven terrain with a prosthetic can be incredibly challenging. That’s why scientists are turning to robotics and artificial intelligence (AI) to take artificial limbs one step further, giving them the ability to sense what a wearer is about to do.
Researchers from the University of Michigan unveiled an AI-powered prosthetic leg in 2019 that could sense the contractions in its wearer’s muscles to know if they planned to start walking up stairs or down a ramp. Now, a team from North Carolina State University has developed a computer vision system that gives a prosthetic leg the ability to not only “see” what’s ahead, but also calculate its level of certainty in that prediction.
For their study, published in the journal IEEE Transactions on Automation Science and Engineering, the NC State researchers taught an AI to see the difference between six types of terrain: tile, brick, concrete, grass, “upstairs,” and “downstairs.” To train the AI to predict where it was headed, they walked around both inside and outdoors, while wearing cameras mounted on eyeglasses and on their own legs. “We found that using both cameras worked well, but required a great deal of computing power and might be cost-prohibitive,” researcher Helen Huang said in a news release.
The team designed their system to work with existing prosthetics — just add a camera. They have yet to actually test it on a robotic prosthetic leg, but they plan to do that next. While a computer vision system that can predict what’s ahead of a prosthetic leg wearer would be impressive on its own, the NC State researchers gave their AI an extra ability: it makes a prediction, then calculates its level of certainty in that prediction and uses that to decide how to adjust its behavior.
“If the degree of uncertainty is too high, the AI isn’t forced to make a questionable decision — it could instead notify the user that it doesn’t have enough confidence in its prediction to act, or it could default to a ‘safe’ mode,” Boxuan Zhong said.
The researchers believe this ability to factor in uncertainty could make their AI useful for applications far beyond prosthetics.
