Fes cycling and closed-loop feedback control for rehabilitative human–robot interaction

Christian Cousin, Victor Duenas, Warren Dixon

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

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. Tradeoffs 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.

Original languageEnglish (US)
Article number61
JournalRobotics
Volume10
Issue number2
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Adaptive control
  • Cycling
  • FES
  • Human–robot interaction
  • NMES
  • Nonlinear control
  • Rehabilitation
  • Robotics

ASJC Scopus subject areas

  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence

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