skip to main content

Title: Shared Control of a Powered Exoskeleton and Functional Electrical Stimulation Using Iterative Learning
A hybrid exoskeleton comprising a powered exoskeleton and functional electrical stimulation (FES) is a promising technology for restoration of standing and walking functions after a neurological injury. Its shared control remains challenging due to the need to optimally distribute joint torques among FES and the powered exoskeleton while compensating for the FES-induced muscle fatigue and ensuring performance despite highly nonlinear and uncertain skeletal muscle behavior. This study develops a bi-level hierarchical control design for shared control of a powered exoskeleton and FES to overcome these challenges. A higher-level neural network–based iterative learning controller (NNILC) is derived to generate torques needed to drive the hybrid system. Then, a low-level model predictive control (MPC)-based allocation strategy optimally distributes the torque contributions between FES and the exoskeleton’s knee motors based on the muscle fatigue and recovery characteristics of a participant’s quadriceps muscles. A Lyapunov-like stability analysis proves global asymptotic tracking of state-dependent desired joint trajectories. The experimental results on four non-disabled participants validate the effectiveness of the proposed NNILC-MPC framework. The root mean square error (RMSE) of the knee joint and the hip joint was reduced by 71.96 and 74.57%, respectively, in the fourth iteration compared to the RMSE in the 1st sit-to-stand iteration.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Frontiers in Robotics and AI
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Introduction

    Individuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.


    In this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories.


    The MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone.


    To realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.

    more » « less
  2. null (Ed.)
    Functional electrical stimulation (FES) is a potential technique for reanimating paralyzed muscles post neurological injury/disease. Several technical challenges including difficulty in measuring and compensating for delayed muscle activation levels inhibit its satisfactory control performance. In this paper, an ultrasound (US) imaging approach is proposed to measure delayed muscle activation levels under the implementation of FES. Due to low sampling rates of US imaging, a sampled data observer (SDO) is designed to estimate the muscle activation in a continuous manner. The SDO is combined with continuous-time dynamic surface control (DSC) approach that compensates for the electromechanical delay (EMD) in the tibialis anterior (TA) activation dynamics. The stability analysis based on the Lyapunov-Krasovskii function proves that the SDO-based DSC plus delay compensation (SDO-DSC-DC) approach achieves semi-global uniformly ultimately bounded (SGUUB) tracking performance. Simulation results on an ankle dorsiflexion neuromusculoskeletal system show the root mean square error (RMSE) of desired trajectory tracking is reduced by 19.77 % by using the proposed SDO-DSC-DC compared to the DSC-DC without the SDO. The findings provide potentials for rehabilitative devices, like powered exoskeleton and FES, to assist or enhance human limb movement based on the corresponding muscle activities in real-time. 
    more » « less
  3. Task-specific, trajectory-based control methods commonly used in exoskeletons may be appropriate for individuals with paraplegia, but they overly constrain the volitional motion of individuals with remnant voluntary ability (representing a far larger population). Human-exoskeleton systems can be represented in the form of the Euler-Lagrange equations or, equivalently, the port-controlled Hamiltonian equations to design control laws that provide task-invariant assistance across a continuum of activities/environments by altering energetic properties of the human body. We previously introduced a port-controlled Hamiltonian framework that parameterizes the control law through basis functions related to gravitational and gyroscopic terms, which are optimized to fit normalized able-bodied joint torques across multiple walking gaits on different ground inclines. However, this approach did not have the flexibility to reproduce joint torques for a broader set of activities, including stair climbing and stand-to-sit, due to strict assumptions related to input-output passivity, which ensures the human remains in control of energy growth in the closed-loop dynamics. To provide biomimetic assistance across all primary activities of daily life, this paper generalizes this energy shaping framework by incorporating vertical ground reaction forces and global planar orientation into the basis set, while preserving passivity between the human joint torques and human joint velocities. We present an experimental implementation on a powered knee-ankle exoskeleton used by three able-bodied human subjects during walking on various inclines, ramp ascent/descent, and stand-to-sit, demonstrating the versatility of this control approach and its effect on muscular effort. 
    more » « less
  4. null (Ed.)
    Powered ankle exoskeletons that apply assistive torques with optimized timing and magnitude can reduce metabolic cost by ∼10% compared to normal walking. However, finding individualized optimal control parameters is time consuming and must be done independently for different walking modes (e.g., speeds, slopes). Thus, there is a need for exoskeleton controllers that are capable of continuously adapting torque assistance in concert with changing locomotor demands. One option is to use a biologically inspired, model-based control scheme that can capture the adaptive behavior of the human plantarflexors during natural gait. Here, based on previously demonstrated success in a powered ankle-foot prosthesis, we developed an ankle exoskeleton controller that uses a neuromuscular model (NMM) comprised of a Hill type musculotendon driven by a simple positive force feedback reflex loop. To examine the effects of NMM reflex parameter settings on (i) ankle exoskeleton mechanical performance and (ii) users’ physiological response, we recruited nine healthy, young adults to walk on a treadmill at a fixed speed of 1.25 m/s while donning bilateral tethered robotic ankle exoskeletons. To quantify exoskeleton mechanics, we measured exoskeleton torque and power output across a range of NMM controller Gain (0.8–2.0) and Delay (10–40 ms) settings, as well as a High Gain/High Delay (2.0/40 ms) combination. To quantify users’ physiological response, we compared joint kinematics and kinetics, ankle muscle electromyography and metabolic rate between powered and unpowered/zero-torque conditions. Increasing NMM controller reflex Gain caused increases in average ankle exoskeleton torque and net power output, while increasing NMM controller reflex Delay caused a decrease in net ankle exoskeleton power output. Despite systematic reduction in users’ average biological ankle moment with exoskeleton mechanical assistance, we found no NMM controller Gain or Delay settings that yielded changes in metabolic rate. Post hoc analyses revealed weak association at best between exoskeleton and biological mechanics and changes in users’ metabolic rate. Instead, changes in users’ summed ankle joint muscle activity with powered assistance correlated with changes in their metabolic energy use, highlighting the potential to utilize muscle electromyography as a target for on-line optimization in next generation adaptive exoskeleton controllers. 
    more » « less
  5. null (Ed.)
    Task-invariant control methods for powered exoskeletons provide flexibility in assisting humans across multiple activities and environments. Energy shaping control serves this purpose by altering the human body’s dynamic characteristics in closed loop. Our previous work on potential energy shaping alters the gravitational vector to reduce the user’s perceived gravity, but this method cannot provide velocity-dependent assistance. The interconnection and damping assignment passivity-based control (IDA-PBC) method provides more freedom to shape a dynamical system’s energy through the interconnection structure of a port-controlled Hamiltonian system model. This paper derives a novel energetic control strategy based on IDA-PBC for a backdrivable knee-ankle exoskeleton. The control law provides torques that depend on various basis functions related to gravitational and gyroscopic terms. We optimize a set of constant weighting parameters for these basis functions to obtain a control law that produces able-bodied joint torques during walking on multiple ground slopes. We perform experiments with an able-bodied human subject wearing a knee-ankle exoskeleton to demonstrate reduced activation in certain lower-limb muscles. 
    more » « less