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Data-driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury
  • Derek Wolf ,
  • Antonie J. (Ton) van den Bogert ,
  • Eric M. Schearer
Derek Wolf
Vanderbilt University, Vanderbilt University

Corresponding Author:[email protected]

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Antonie J. (Ton) van den Bogert
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Eric M. Schearer
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Abstract

Functional electrical stimulation (FES) is a promising technology for restoring reaching motions to individuals with upper-limb paralysis caused by a spinal cord injury (SCI). However, the limited muscle capabilities of an individual with SCI have made achieving FES-driven reaching difficult. We developed a novel trajectory optimization method that used experimentally measured muscle capability data to find feasible reaching trajectories. In a simulation based on a real-life individual with SCI, we compared our method to attempting to follow naive direct-totarget paths. We tested our trajctory planner with three control structures that are commonly used in applied FES: feedback, feedforward-feedback, and model predictive control. Overall, trajectory optimization improved the ability to reach targets and improved the accuracy for the feedforward-feedback and model predictive controllers (p < 0.001). The trajectory optimization method should be practically implemented to improve the FESdriven reaching performance.
2023Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering volume 31 on pages 2246-2256. 10.1109/TNSRE.2023.3272929