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Using Footsteps to Estimate Changes in the Desired Gait Speed of an Exoskeleton User | IEEE Journals & Magazine | IEEE Xplore

Using Footsteps to Estimate Changes in the Desired Gait Speed of an Exoskeleton User


Abstract:

This letter outlines an estimation framework to detect changes in the intended gait speed of an assistive exoskeleton user during walking. A twice-per-step estimation str...Show More

Abstract:

This letter outlines an estimation framework to detect changes in the intended gait speed of an assistive exoskeleton user during walking. A twice-per-step estimation strategy, termed a Buttressed Kalman Filter, is presented to leverage changes in foot placement to infer changes in desired speed. The first stage of the estimator applies a Bayesian update to the center of mass state at midstance before it is passed to a Kalman filter in the second stage. The Bayesian update relies on the comparison between a predicted step length computed as a function of the intended velocity and the measured step length, the difference of which provides insight into user intent. This framework was tested with sensor data acquired from walking trials in an Ekso GT exoskeleton for users with and without incomplete Spinal Cord Injuries (iSCIs) from the middle to lower spine. The trials consisted of users changing their gait speed upon command. The presented framework was able to anticipate these desired changes before users physically changed their speed. It was also found that using measurements of the root mean square (RMS) current of the hip motors increased the effectiveness of the estimator in predicting intent changes for individuals with iSCIs.
Published in: IEEE Robotics and Automation Letters ( Volume: 6, Issue: 4, October 2021)
Page(s): 6781 - 6788
Date of Publication: 09 July 2021

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