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1. Cadence Tracking for Switched FES-Cycling With Unknown Time-Varying Input Delay

   https://doi.org/10.1115/DSCC2019-9078  

   Allen, B.; Cousin, C.; Rouse, C.; Dixon, W. (October 2019, ASME 2019 Dynamic Systems and Control Conference)

   Functional electrical stimulation (FES) induced exercise, such as motorized FES-cycling, is commonly used in rehabilitation for lower limb movement disorders. A challenge in closed-loop FES control is the presence of an input delay between the application (and removal) of the electrical stimulus and the production of muscle force. Moreover, switching between motor control and FES control of various muscle groups can be destabilizing. This paper examines the development of a control method and state-dependent trigger condition to account for the time-varying input delayed response. Uniformly ultimately bounded tracking for a switched uncertain nonlinear dynamic system with input delays is achieved. 

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2. Adaptive Trajectory Tracking During Motorized and FES-Induced Biceps Curls via Integral Concurrent Learning

   https://doi.org/10.1115/DSCC2020-3125  

   Allen, Brendon C.; Stubbs, Kimberly J.; Dixon, Warren E. (October 2020, ASME Dynamic Systems and Control Conference)

   null (Ed.)

   A common rehabilitative technique for those with neuro-muscular disorders is functional electrical stimulation (FES) induced exercise such as FES-induced biceps curls. FES has been shown to have numerous health benefits, such as increased muscle mass and retraining of the nervous system. Closed-loop control of a motorized FES system presents numerous challenges since the system has nonlinear and uncertain dynamics and switching is required between motor and FES control, which is further complicated by the muscle having an uncertain control effectiveness. An additional complication of FES systems is that high gain feedback from traditional robust controllers can be uncomfortable to the participant. In this paper, data-based, opportunistic learning is achieved by implementing an integral concurrent learning (ICL) controller during a motorized and FES-induced biceps curl exercise. The ICL controller uses adaptive feedforward terms to augment the FES controller to reduce the required control input. A Lyapunov-based analysis is performed to ensure exponential trajectory tracking and opportunistic, exponential learning of the uncertain human and machine parameters. In addition to improved tracking performance and robustness, the potential of learning the specific dynamics of a person during a rehabilitative exercise could be clinically significant. Preliminary simulation results are provided and demonstrate an average position error of 0.14 ± 1.17 deg and an average velocity error of 0.004 ± 1.18 deg/s. 

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3. Cadence and Position Tracking for Decoupled Legs during Switched Split-Crank Motorized FES-Cycling

   Esquivel Estay, Fidel; Rouse, Courtney; Cohen, Max; Cousin, Christian; Dixon, Warren E. (July 2019, Proc. American Control Conference)

   Functional electrical stimulation (FES) has proven to be an effective method for improving health and regaining muscle function for people with limited or reduced motor skills. Closed-loop control of motorized FES-cycling can facilitate recovery. Many people with movement disorders (e.g., stroke) have asymmetries in their motor control, motivating the need for a closed-loop control system that can be implemented on a split-crank cycle. In this paper, nonlinear sliding mode controllers are designed for the FES and electric motor on each side of a split-crank cycle to maintain a desired cadence and a crank angle offset of 180 degrees, simulating standard pedaling conditions. A Lyapunov-like function is used to prove stability and tracking of the desired cadence and position for the combined cycle-rider system. One experimental trial on an able-bodied individual demonstrated the feasibility and stability of the closed-loop controller, which resulted in an average cadence error of 2.62 ± 3.54 RPM for the dominant leg and an average position and cadence error of 39.84±10.77 degrees and −0.04 ± 8.79 RPM for the non-dominant leg. 

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4. Saturated Control of a Switched FES-Cycle with an Unknown Time-Varying Input Delay

   Allen, B. C.; Stubbs, K. J.; Dixon, W. E. (December 2020, IFAC Conference on Cyber-Physical Human-Systems)

   A common rehabilitation for those with lower limb movement disorders is motorized functional electrical stimulation (FES) induced cycling. Motorized FES-cycling is a switched system with uncertain dynamics, unknown disturbances, and there exists an unknown time-varying input delay between the application/removal of stimulation and the onset/removal of muscle force. This is further complicated by the fact that each participant has varying levels of sensitivity to the FES input, and the stimulation must be bounded to ensure comfort and safety. In this paper, saturated FES and motor controllers are developed for an FES-cycle that ensure safety and comfort of the participant, while likewise being robust to uncertain parameters in the dynamics, unknown disturbances, and an unknown time-varying input delay. A Lyapunov-based stability analysis is performed to ensure uniformly ultimately bounded cadence tracking. 

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5. Switched Control of Motor Assistance and Functional Electrical Stimulation for Biceps Curls

   https://doi.org/10.3390/app10228090  

   Rouse, Courtney; Allen, Brendon; Dixon, Warren (November 2020, Applied Sciences)

   null (Ed.)

   Rehabilitation robotics is an emerging tool for motor recovery from various neurological impairments. However, balancing the human and robot contribution is an open problem. While the motor input can reduce fatigue, which is often a limiting factor of functional electrical stimulation (FES) exercises, too much assistance can slow progress. For a person with a neurological impairment, FES can assist by strategically contracting their muscle(s) to achieve a desired limb movement; however, feasibility can be limited due to factors such as subject comfort, muscle mass, unnatural muscle fiber recruitment, and stimulation saturation. Thus, motor assistance in addition to FES can be useful for prolonging exercise while still ensuring physical effort from the person. In this paper, FES is applied to the biceps brachii to perform biceps curls, and motor assistance is applied intermittently whenever the FES input reaches a pre-set comfort threshold. Exponential stability of the human–robot system is proven with a Lyapunov-like switched systems stability analysis. Experimental results from participants with neurological conditions demonstrate the feasibility and performance of the controller. 

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