Exoskeletons use electric motors to provide extra power to a user’s limbs when carrying out strenuous activities, typically designed to support well-defined activities, such as walking or climbing stairs.
A new approach from researchers at the Georgia Institute of Technology uses AI neural networks to seamlessly adapt an exoskeleton’s sensors to a user’s particular posture and pace of activity.
The team trained the neural network with data from 25 participants performing a variety of strenuous activities while wearing the exoskeleton.
Results show that the concept is quite adaptable and that exoskeletons could soon become an “off-the-shelf” product for a wide range of strenuous activities.
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