Limb-assistive device with machine learning
AssigneeThe Regents of the University of Michigan
InventorsRoberto Manuel Leonardo MEDRANO, Gray C. THOMAS, Robert D. GREGG, IV, Elliott J. ROUSE
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Abstract
A powered limb-assistive device includes a controller that uses a neural network to generate an initial prediction of the current gait state of a user of the device based on kinematic measurements from the device. The controller filters the initial prediction to arrive at a current prediction of the current gait state based at least in part on a continually updated measure of trust in the kinematic measurements. The controller can be employed in a powered prosthesis or orthosis, such as a powered exoskeleton that assists user movement of a first portion of their leg relative to a second portion of their leg about a knee and/or ankle joint.
Claims11
A powered limb-assistive device comprising a controller that uses a neural network to generate an initial prediction of a current gait state of a user of the device based on kinematic measurements from the device and then filters the initial prediction to arrive at a current prediction of the current gait state of the user based at least in part on a continually updated measure of trust in the kinematic measurements.
Dependencies are inferred from the claim text.