FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction
For individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Robotics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-6581/10/2/61 |
| _version_ | 1797536713735667712 |
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| author | Christian Cousin Victor Duenas Warren Dixon |
| author_facet | Christian Cousin Victor Duenas Warren Dixon |
| author_sort | Christian Cousin |
| collection | DOAJ |
| description | For individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in intimately coordinated human–robot interaction. An example of such interaction is FES cycling, where motorized assistance can provide high-intensity and repetitive practice of coordinated limb motion, resulting in physiological and functional benefits. In this paper, the development of multiple FES cycling testbeds and safeguards is described, along with the switched nonlinear dynamics of the cycle–rider system. Closed-loop FES cycling control designs are described for cadence and torque tracking. For each tracking objective, the authors’ past work on robust and adaptive controllers used to compute muscle stimulation and motor current inputs is presented and discussed. Experimental results involving both able-bodied individuals and participants with neurological injuries are provided for each combination of controller and tracking objective. Trade-offs for the control algorithms are discussed based on the requirements for implementation, desired rehabilitation outcomes and resulting rider performance. Lastly, future works and the applicability of the developed methods to additional technologies including teleoperated robotics are outlined. |
| first_indexed | 2024-03-10T12:04:44Z |
| format | Article |
| id | doaj.art-6808aadbf1544572bb88497c251c1395 |
| institution | Directory Open Access Journal |
| issn | 2218-6581 |
| language | English |
| last_indexed | 2024-03-10T12:04:44Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Robotics |
| spelling | doaj.art-6808aadbf1544572bb88497c251c13952023-11-21T16:38:58ZengMDPI AGRobotics2218-65812021-04-011026110.3390/robotics10020061FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot InteractionChristian Cousin0Victor Duenas1Warren Dixon2Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487, USADepartment of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY 13244, USADepartment of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USAFor individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in intimately coordinated human–robot interaction. An example of such interaction is FES cycling, where motorized assistance can provide high-intensity and repetitive practice of coordinated limb motion, resulting in physiological and functional benefits. In this paper, the development of multiple FES cycling testbeds and safeguards is described, along with the switched nonlinear dynamics of the cycle–rider system. Closed-loop FES cycling control designs are described for cadence and torque tracking. For each tracking objective, the authors’ past work on robust and adaptive controllers used to compute muscle stimulation and motor current inputs is presented and discussed. Experimental results involving both able-bodied individuals and participants with neurological injuries are provided for each combination of controller and tracking objective. Trade-offs for the control algorithms are discussed based on the requirements for implementation, desired rehabilitation outcomes and resulting rider performance. Lastly, future works and the applicability of the developed methods to additional technologies including teleoperated robotics are outlined.https://www.mdpi.com/2218-6581/10/2/61rehabilitationFESNMESroboticshuman–robot interactionnonlinear control |
| spellingShingle | Christian Cousin Victor Duenas Warren Dixon FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction Robotics rehabilitation FES NMES robotics human–robot interaction nonlinear control |
| title | FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction |
| title_full | FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction |
| title_fullStr | FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction |
| title_full_unstemmed | FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction |
| title_short | FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction |
| title_sort | fes cycling and closed loop feedback control for rehabilitative human robot interaction |
| topic | rehabilitation FES NMES robotics human–robot interaction nonlinear control |
| url | https://www.mdpi.com/2218-6581/10/2/61 |
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