After years of development, the Stanford Biomechatronics Laboratory—led by Steve Collins, associate professor of mechanical engineering—has created a boot-like exoskeleton that results in exceptional improvements in walking speed and energy economy (9% faster with 17% less energy expended per distance travelled, to be exact).
Now that the exoskeleton has proven itself in the wild, outside of the lab, it could transform the lives of older adults and people who are beginning to experience mobility decline due to disability.
With each stride, the user of the robotic boot receives a push from a motor that cooperates with their calf muscles, giving them a noticeable spring in their step. The push is customised for each wearer of the gadget since it uses a machine-learning algorithm. In actuality, the exoskeleton can be tailored to a new user in just one hour of walking. To understand how the way an individual walks with the exoskeleton corresponds to how much energy they are consuming, the team's machine learning model is built on years of motion and energy expenditure data collection.
They have been working toward this objective for almost 20 years, and Collins admits that they are a bit surprised that we were ultimately successful. "Many individuals are going to benefit from this technology,"
