Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury
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 dev...
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| Main Authors: | , , |
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| Format: | Book |
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IEEE,
2023-01-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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| Summary: | 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-to-target paths. We tested our trajectory 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 (<inline-formula> <tex-math notation="LaTeX">${p}< {0}.{001}$ </tex-math></inline-formula>). The trajectory optimization method should be practically implemented to improve the FES-driven reaching performance. |
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| Item Description: | 1558-0210 10.1109/TNSRE.2023.3272929 |