An exoskeleton that helps to walk faster with less effort, this is what a team from the Stanford biomechatronics laboratory has revealed.
The Stanford laboratory team revealed, in the journal Nature, the result of several years of work: an exoskeleton in the form of a robotic boot capable of adapting to its wearer, thanks to a model based on machine learning. This creation is based on a simple principle: everyone walks differently.
How does this exoskeleton work?
Support exoskeletons are nothing new. They have been around for years, but the main obstacle has always been individualization. Stanford researchers have managed to overcome this major problem, with this robotic boot that can adapt to its wearer.
Using built-in wearable sensors that will measure ankle strength and movement, the boot will provide more precise assistance. It only takes an hour for the device to start customizing how it assists the wearer. The boot is also equipped with a motor working with the calf muscles, allowing the patient to be given additional impetus with each step.
The team claims that the energy savings and increased speed would be equivalent to removing a 30-pound (nearly 15 kg) backpack. ” Optimized assist enabled people to walk 9% faster with 17% less energy expended per distance walked, compared to walking in normal shoes adds Steve Collins, one of the researchers.
Why this robotic boot?
Obviously, the goal of this robotic boot, in the long term, would be to help people with reduced mobility to move around. This includes the elderly and those with disabilities resulting in a decline in their mobility. ” We have been working towards this goal for about 20 years », explains the team.
This model could be commercialized in the years to come, according to the Stanford researchers, precisely because they managed to overcome the obstacle of individualization, unlike existing exoskeletons which did not take into account the strength of each patient.
The team also plans to design variants of the boot, which can improve balance or even reduce joint pain.
Source : Techcrunch
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