Data-Based and Opportunistic Integral Concurrent Learning for Adaptive Trajectory Tracking During Switched FES-Induced Biceps Curls
Author:
Affiliation:
1. Department of Mechanical Engineering, Auburn University, Auburn, AL, USA
2. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA
Funder
National Defense Science and Engineering Graduate Fellowship Program
Assistant Secretary of Defense for Health Affairs, through the Congressionally Directed Medical Research Program
NSF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
https://ieeexplore.ieee.org/ielam/7333/9695946/9875948-aam.pdf
Reference34 articles.
1. Robust Cadence Tracking for Switched FES-Cycling With an Unknown Time-Varying Input Delay
2. Position and cadence tracking of a motorized FES-cycle with an unknown time-varying input delay using saturated FES control
3. LaSalle-Yoshizawa Corollaries for Nonsmooth Systems
4. Differential equations with discontinuous right-hand side
5. Characterization of the Time-Varying Nature of Electromechanical Delay During FES-Cycling
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