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1. Cycling With Functional Electrical Stimulation and Adaptive Neural Network Admittance Control

   Cousin, Christian ; Deptula, Patryk ; Rouse, Courtney ; Dixon, Warren E. ( July 2019 , Proc. American Control Conference)

   For individuals with neurological conditions (NCs) affecting the muscles of their legs, motorized functional electrical stimulation (FES) cycling is a rehabilitation strategy which offers numerous health benefits. Motorized FES cycling is an example of cooperative physical human-robot interaction where both the cycle’s motor and rider’s muscles (through electrical stimulation) must be well controlled to achieve desired performance. Since every NC is unique, adaptive control of motorized FES cycling is motivated over a one-size-fits-all approach. In this paper, a robust sliding-mode controller is employed on the rider’s muscles while an adaptive neural network admittance controller is employed on the cycle’s motor to preserve rider comfort and safety. Through a Lyapunov-like switched systems stability analysis, global asymptotic stability of the cycle controller is guaranteed and the muscle controller is proven to be passive with respect to the cycle. Experiments on one able-bodied participant were conducted to validate the control design. 

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2. Cadence and Admittance Control of a Motorized Functional Electrical Stimulation Cycle

   https://doi.org/10.1109/CDC.2018.8618685  

   Cousin, Christian A. ; Duenas, Victor H. ; Rouse, Courtney A. ; Dixon, Warren E. ( December 2018 , Proc. IEEE Conference on Decision and Control)

   Functional electrical stimulation (FES) can be combined with a motorized cycle to offer various rehabilitation options for individuals with neurological conditions. Typically, FES cycling controllers use cooperating muscles and an electric motor to track cadence. In this paper, in addition to cooperative cadence tracking, the motorized cycle tracks an admittance trajectory generated using torque feedback. This method allows the cycle to deviate from the desired cadence trajectory and admit to the rider-applied torque, ensuring safe human-machine interaction. Two sets of uncertain, nonlinear dynamics are presented, one for the human rider and one for the robot, linked by a common measurable interaction torque. After developing cadence and admittance controllers, a Lyapunov-like switched system stability analysis is provided to prove global exponential tracking of the cadence error system, and a passivity analysis is conducted to prove passivity of the cycle’s admittance controller with respect to the rider’s interaction torque. *Note this paper does not properly cite the specific project. 

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3. Admittance Control of a Teleoperated Motorized Functional Electrical Stimulation Rehabilitation Cycle

   K. J. Stubbs, B. C. ( December 2020 , IFAC Conference on Cyber-Physical Human-Systems)

   null (Ed.)

   A bilateral teleoperated rehabilitation cycling system is developed for people with movement impairments due to various neurological disorders. A master hand-cycling device is used by the operator to set the desired position and cadence of a lower-body functional electrical stimulation (FES) controlled and motor assisted recumbent cycle. The master device also uses kinematic haptic feedback to reflect the lower-body cycle's dynamic response to the operator. To accommodate for the unknown nonlinear dynamics inherent to physical human machine interaction (pHMI), admittance controllers were developed to indirectly track desired interaction torques for both the haptic feedback device and the lower-body cycle. A robust position and cadence controller, which is only active within the regions of the crank cycle where FES produces sufficient torque values, was used to determine the FES intensity. A Lyapunov analysis is used to prove the robust FES controller yields global exponential tracking to the desired position and cadence set by the master device within FES stimulation regions. Outside of the FES regions, the admittance controllers at the hands and legs work in conjunction to produce desired performance. Both admittance controllers were analyzed for the entire crank cycle, and found to be input/output strictly passive and globally exponentially stable in the absence of human effort, despite the uncertain nonlinear dynamics. 

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4. Stable Cadence Tracking of Admitting Functional Electrical Stimulation Cycle

   https://doi.org/10.1115/DSCC2018-8989  

   Cousin, Christian A. ; Duenas, Victor H. ; Rouse, Courtney A. ; Dixon, Warren E. ( September 2018 , Proc. ASME Dynamic Systems and Control Conference)

   Rehabilitation robotics and functional electrical stimulation (FES) are two promising methods of rehabilitation for people with neurological disorders. In motorized FES cycling, both the rider and the motorized cycle must be controlled for cooperative human-machine interaction. While rehabilitation goals vary widely, FES cycling traditionally rejects rider disturbances to accomplish cadence and power tracking; however, this paper ensures that the cycle accommodates the rider without rejecting rider disturbances as a means to promote function and strength recovery while ensuring rider safety. A cadence and admittance controller are developed to activate the cycle’s electric motor and the rider’s leg muscles through FES when kinematically efficient. Using a single set of combined cycle-rider dynamics, a Lyapunov-like switched systems analysis is conducted to conclude global exponential cadence tracking. A subsequent passivity analysis is conducted to show the admittance controller is passive with respect to the rider. For a desired cadence of 50 RPM, preliminary experiments on one able-bodied participant and one participant with spina bifida demonstrate tracking errors of −0.07±2.59 RPM and −0.20±3.86 RPM, respectively. *Note this paper does not properly cite the specific NSF project number. 

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5. FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction

   https://doi.org/10.3390/robotics10020061  

   Cousin, Christian ; Duenas, Victor ; Dixon, Warren ( June 2021 , Robotics)

   null (Ed.)

   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. 

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