ABSTRACT
OBJECTIVE: The objective of this paper was to develop and test a novel control algorithm that enables stroke survivors to pedal a cycle in a desired cadence range despite varying levels of functional abilities after stroke. METHODS: A novel algorithm was developed which automatically adjusts 1) the intensity of functional electrical stimulation (FES) delivered to the leg muscles, and 2) the current delivered to an electric motor. The algorithm automatically switches between assistive, uncontrolled, and resistive modes to accommodate for differences in functional impairment, based on the mismatch between the desired and actual cadence. Lyapunov-based methods were used to theoretically prove that the rider's cadence converges to the desired cadence range. To demonstrate the controller's real-world performance, nine chronic stroke survivors performed two cycling trials: 1) volitional effort only and 2) volitional effort accompanied by the control algorithm assisting and resisting pedaling as needed. RESULTS: With a desired cadence range of 50-55 r/min, the developed controller resulted in an average rms cadence error of 1.90 r/min, compared to 6.16 r/min during volitional-only trials. CONCLUSION: Using FES and an electric motor with a two-sided cadence control objective to assist and resist volitional efforts enabled stroke patients with varying strength and abilities to pedal within a desired cadence range. SIGNIFICANCE: A protocol design that constrains volitional movements with assistance and resistance from FES and a motor shows potential for FES cycles and other rehabilitation robots during stroke rehabilitation.
Subject(s)
Algorithms , Bicycling/physiology , Electric Stimulation/methods , Stroke Rehabilitation/methods , Adult , Aged , Female , Humans , Male , Middle Aged , Nonlinear Dynamics , Robotics , Young AdultABSTRACT
For an individual suffering from a neurological condition, such as spinal cord injury, traumatic brain injury, or stroke, motorized functional electrical stimulation (FES) cycling is a rehabilitation strategy, which offers numerous health benefits. Motorized FES cycling is an example of physical human-robot interaction in which both systems must be controlled; the human is actuated by applying neuromuscular electrical stimulation to the large leg muscle groups, and the cycle is actuated through its onboard electric motor. While the rider is stimulated using a robust sliding-mode controller, the cycle utilizes an admittance controller to preserve rider safety. The admittance controller is shown to be passive with respect to the rider, and the cadence controller is shown to be globally exponentially stable through a Lyapunov-like switched systems stability analysis. Experiments are conducted on three able-bodied participants and four participants with neurological conditions (NCs) to demonstrate the efficacy of the developed controller and investigate the effect of manipulating individual admittance parameters. Results demonstrate an average admittance cadence error of -0.06±1.47 RPM for able-bodied participants and -0.02 ± 0.93 RPM for participants with NCs.
Subject(s)
Bicycling/physiology , Electric Stimulation Therapy/methods , Rehabilitation/methods , Adult , Algorithms , Female , Humans , Male , Middle Aged , Muscle, Skeletal/physiology , Nervous System Diseases/rehabilitation , Patient Safety , Robotics , Spinal Cord Injuries/rehabilitation , Treatment Outcome , Young AdultABSTRACT
Functional electrical stimulation (FES) can help individuals with physical disabilities by assisting limb movement; however, the change in muscle geometry associated with limb movement may affect the response to stimulation. The aim of this paper was to quantify the effects of elbow flexion and stimulation site on muscle torque production. Contraction torque about the elbow was measured in 12 healthy individuals using a custom elbow flexion testbed and a transcutaneous electrode array. Stimulation was delivered to six distinct sites along the biceps brachii over 11 elbow flexion angles. Flexion angle was found to significantly influence the optimal (i.e., torque-maximizing) stimulation site ( ), with post hoc analysis indicating a proximal shift in optimal stimulation site with increased flexion. Similarly, the biceps stimulation site was found to significantly influence the flexion angle at which peak torque occurred ( ), with post hoc analysis indicating an increase in peak-torque flexion angle as stimulation site is moved proximally up the biceps. Since maximizing muscle force per unit stimulation is a common goal in rehabilitative FES, future efforts could examine methods which compensate for the shift in optimal stimulation site during FES-induced limb movement.
Subject(s)
Elbow/physiology , Electric Stimulation , Muscle, Skeletal/physiology , Adult , Arm , Biomechanical Phenomena , Electrodes , Electromyography , Female , Healthy Volunteers , Humans , Male , Muscle Contraction , Torque , Young AdultABSTRACT
Two common rehabilitation therapies for individuals possessing neurological conditions are functional electrical stimulation (FES) and robotic assistance. This paper focuses on combining the two rehabilitation strategies for use on the biceps brachii muscle group. FES is used to elicit muscle contractions to actuate the forearm and a rehabilitation robot is used to challenge the muscle group in its efforts. Two controllers were developed and implemented to accomplish the multifaceted objective, both of which achieve global exponential stability for position and torque tracking as proven through a Lyapunov stability analysis. Experiments performed on one able bodied individual demonstrate an average RMS error of 5.8 degrees for position tracking and 0.40 Newton-meters for torque tracking.
