Control of FES-induced cyclical movements of the lower leg

Modelling the Optimal Control of Cyclical Leg Movements Induced by Functional Electrical Stimulation

An optimal control strategy for FES-induced cyclical leg movements in paraplegics is proposed. The control of the cyclical movement of a freely swinging leg is considered as an example. Quadriceps and the flexion withdrawal reflex are stimulated in order to generate a cyclical movement, of which the forward swing resembles the swing phase of gait. Optimal stimulation patterns are determined on the basis of an optimization criterion and a dynamic model of the system. The criterion is based on desired movement parameters and a minimal duration of the stimulation bursts. The movement parameters should ensure the generation of the desired cyclical movement: a desired hip angle range, sufficient foot clearance during the forward swing and knee extension at the beginning of the backward swing. Minimal duration of the stimulation bursts is assumed to yield minimal fatigue. A dynamic model, describing the dynamics of the neural system, the muscles and the leg, was constructed and its parameters identified on the basis of preliminary experiments and literature. Optimal timing of the quadriceps and flexion reflex stimulation bursts was determined by means of computer simulation. These simulations predicted that the flexion reflex should be stimulated in a short burst approximately 150 ms before the start of the forward swing. The quadriceps should be stimulated approximately starting 200 ms before the end of the forward swing in order to ensure knee extension at the beginning of the backward swing. The duration of one cycle of the movement was between 1300 and 1500 ms in these simulations. These results predict that the movement specified by the functional objectives can be realised using only two channels of stimulation. On the basis of the optimal timing, an adaptive control strategy can be designed, which varies the stimulation burst width when muscles fatigue.

Control of Dynamic Limb Motion Using Fatigue-Resistant Asynchronous Intrafascicular Multi-Electrode Stimulation

Asynchronous intrafascicular multi-electrode stimulation (aIFMS) of small independent populations of peripheral nerve motor axons can evoke selective, fatigue-resistant muscle forces. We previously developed a real-time proportional closed-loop control method for aIFMS generation of isometric muscle force and the present work extends and adapts this closed-loop controller to the more demanding task of dynamically controlling joint position in the presence of opposing joint torque. A proportional-integral-velocity controller, with integrator anti-windup strategies, was experimentally validated as a means to evoke motion about the hind-limb ankle joint of an anesthetized feline via aIFMS stimulation of fast-twitch plantar-flexor muscles. The controller was successful in evoking steps in joint position with 2.4% overshoot, 2.3-s rise time, 4.5-s settling time, and near-zero steady-state error. Controlled step responses were consistent across changes in step size, stable against external disturbances, and reliable over time. The controller was able to evoke smooth eccentric motion at joint velocities up to 8 deg./s, as well as sinusoidal trajectories with frequencies up to 0.1 Hz, with time delays less than 1.5 s. These experiments provide important insights toward creating a robust closed-loop aIFMS controller that can evoke precise fatigue-resistant motion in paralyzed individuals, despite the complexities introduced by aIFMS.

Fatigue of intermittently stimulated paralyzed human quadriceps during imposed cyclical lower leg movements

In this study the torque output of intermittently stimulated paralyzed human knee extensor muscles during imposed isokinetic cyclical lower leg movements was investigated in four paraplegic subjects. During prolonged (10 min) experiments the influence of knee angular velocity and stimulation parameters on fatigue-induced torque decline was studied. Pulse width and amplitude were set to obtain maximal recruitment. The cycle time was maintained constant at 2 s, comparable to a walking cycle. The maximum torque and averaged torque per cycle were estimated to determine the muscle's performance during sustained intermittent stimulation. The overall loss in time of these parameters had a typical exponential decay reaching asymptotic values. Additionally, larger knee velocities resulted in a significantly faster and relatively larger decay of maximum and averaged torque. Also, the rate and relative decrement of torque output during concentric contractions increased with increasing number of pulses in a cycle. Identification trials, determining the (isometric) torque-angle and (isokinetic) torque-angular velocity relation, were performed. The relations appeared to change due to fatigue. The results might be valuable in the design of optimal control systems for functional electrical stimulation which pursue minimization of muscle fatigue. They may contribute to the derivation of a cost criterion, describing muscle fatigue as a function of both joint movement and stimulation parameters.

Fuzzy FES controller using cycle-to-cycle control for repetitive movement training in motor rehabilitation. Experimental tests with wireless system

A prototype of wireless surface electrical stimulation system combined with the fuzzy FES controller was developed for rehabilitation training with functional electrical stimulation (FES). The developed FES system has three features for rehabilitation training: small-sized electrical stimulator for surface FES, wireless connection between controller and stimulators, and between controller and sensors, and the fuzzy FES controller based on the cycle-to-cycle control for repetitive training. The developed stimulator could generate monophasic or biphasic high voltage stimulus pulse and could output stimulation pulses continuously more than 20 hours with 4 AAA batteries. The developed system was examined with neurologically intact subjects and hemiplegic subjects in knee joint control. The maximum knee joint angle was controlled by regulating burst duration of stimulation pulses by the fuzzy controller. In the results of two experiments of knee extension angle control and knee flexion and extension angle control, the maximum angles reached their targets within small number of cycles and were controlled stably in the stimulation cycles after reaching the target. The fuzzy FES controller based on the cycle-to-cycle control worked effectively to reach the target angle and to compensate difference in muscle properties between subjects. The developed wireless surface FES system would be practical in clinical applications of repetitive execution of similar movements of the limbs for motor rehabilitation with FES.

Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks

Background

The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required.

Methods

The error mapping controller (EMC) here proposed uses artificial neural networks (ANNs) both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID) included in an anti wind-up scheme (called PIDAW) and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID). In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out.

Results

The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances.

Conclusion

Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice.

Model-based control of FES-induced single joint movements

A crucial issue of functional electrical stimulation (FES) is the control of motor function by the artificial activation of paralyzed muscles. Major problems that limit the success of current FES systems are the nonlinearity of the target system and the rapid change of muscle properties due to fatigue. In this study, four different strategies, including an adaptive algorithm, to control the movement of the freely swinging shank were developed on the basis of computer simulations and experimentally evaluated on two subjects with paraplegia due to a complete thoracic spinal cord injury. After developing a nonlinear, physiologically based model describing the dynamic behavior of the knee joint and muscles, an open-loop approach, a closed-loop approach, and a combination of both were tested. In order to automate the individual adjustments cited above, we further evaluated the performances of an adaptive feedforward controller. The two parameters chosen for the adaptation were the threshold pulse width and the scaling factor for adjusting the active moment produced by the stimulated muscle to the fitness of the muscle. These parameters have been chosen because of their significant time variability. The first three controllers with fixed parameters yielded satisfactory result. An additional improvement was achieved by applying the adaptive algorithm that could cope with problems due to muscle fatigue, thus permitting on-line identification of critical parameters of the plant. Although the present study is limited to a simplified experimental setup, its applicability to more complex and functional movements can be expected.

Adaptive control of cyclic movements as muscles fatigue using functional neuromuscular stimulation

For individuals with spinal cord injuries, functional neuromuscular stimulation (FNS) systems can be used to activate paralyzed muscles in order to restore function, provide exercise, or assist in movement therapy. In previous work, the pattern generator/pattern shaper (PG/PS) adaptive controller was evaluated on subjects with spinal cord injuries and was able to automatically adjust stimulation parameters to account for individual subject differences and system response nonlinearities. In this study, the PG/PS control system was utilized in extended trials. Results indicated that the controller adapted stimulation patterns in an online manner to account for changes in system properties due to fatigue.

Real-time gait event detection for paraplegic FES walking

A real-time method for the detection of gait events that occur during the electrically stimulated locomotion of paraplegic subjects is described. It consists of a two-level algorithm for the processing of sensor signals and the determination of gait event times. Sensor signals and information about the progression of the stimulator though its pre-specified stimulation "pattern" are processed by a machine intelligence (fuzzy logic) algorithm to determine an initial estimate of the patient's current phase of gait. This is then reviewed and modified by a second algorithm that removes spurious gait estimates, and determines gait event times. These gait event times are known to the system within approximately one-half of a gait cycle. The resulting gait event detection system was successfully evaluated on three subjects. Detection accuracy is not adversely affected by day-to-day gait variability. This work resolved technical and practical issues that previously limited the real time application of these methods. In particular, cosmetically acceptable insole force transducers were used. This gait event detector is designed for use in a real time controller for the automatic adjustment of the intensity and timing of stimulation while the subject is walking using functional electrical stimulation (FES).

Neuroprosthetic applications of electrical stimulation

Neural prostheses are a developing technology that use electrical activation of the nervous system to restore function to individuals with neurological impairment. Neural prostheses function by electrical initiation of action potentials in nerve fibers that carry the signal to an endpoint where chemical neurotransmitters are released, either to affect an end organ or another neuron. Thus, in principle, any end organ under neural control is a candidate for neural prosthetic control. Applications have included stimulation in both the sensory and motor systems and range in scope from experimental trials with single individuals to commercially available devices. Outcomes of motor system neural prostheses include restoration of hand grasp and release in quadriplegia, restoration of standing and stepping in paraplegia, restoration of bladder function (continence, micturition) following spinal cord injury, and electrophrenic respiration in high-level quadriplegia. Neural prostheses restore function and provide greater independence to individuals with disability.

The relationship between electrical stimulus and joint torque: a dynamic model

The knowledge of the behavior of electrically activated muscles is an important requisite for the development of functional electrical stimulation (FES) systems to restore mobility to persons with paralysis. The aim of this work was to develop a model capable of relating electrical parameters to dynamic joint torque for FES applications. The knee extensor muscles, stimulated using surface electrodes, were used for the experimental preparation. Both healthy subjects and people with paraplegia were tested. The dynamics of the lower limb were represented by a nonlinear second order model, which took account of the gravitational and inertial characteristics of the anatomical segments as well as the damping and stiffness properties of the knee joint. The viscous-elastic parameters of the system were identified experimentally through free pendular movements of the leg. Leg movements induced by quadriceps stimulation were acquired too, using a motion analysis system. Results showed that, for the considered experimental conditions, a simple one-pole transfer function is able to model the relationship between stimulus pulsewidth (PW) and active muscle torque. The time constant of the pole was found to depend on the stimulus pattern (ramp or step) while gain was directly dependent on stimulation frequency.

Adaptive neural network control of cyclic movements using functional neuromuscular stimulation

In this study, we evaluated the performance of an adaptive feedforward controller and its ability to automatically develop and customize stimulation patterns for use in functional neuromuscular stimulation (FNS) systems. Results from previous experiments using the pattern generator/pattern shaper (PG/PS) controller to generate isometric contractions demonstrated its ability to adjust stimulation patterns to account for recruitment nonlinearities and muscle dynamics. In this study, the PG/PS controller was tested under isotonic conditions. This evaluation required the PG/PS controller to account for muscle length-tension and force-velocity properties as well as limb dynamics. The performance of the adaptive controller was also compared with that of a proportional-derivative (PD) feedback controller. The PG/PS controller is composed of a neural network system that adaptively filters a periodic signal to produce a muscle stimulation pattern for generating cyclic movements. We used computer-simulated models to determine controller parameters for the PG/PS and PD controller that perform well across a variety of musculoskeletal systems. The controllers were then experimentally evaluated on both legs of two subjects with spinal cord injury. Results indicated that the PG/PS controller was able to achieve and maintain better tracking performance than the PD controller. This study indicates that the PG/PS control system may provide an effective mechanism for automatically customizing stimulation patterns for individuals using FNS systems.

Model-based development of neuroprosthesis for paraplegic patients

In paraplegic patients with upper motor neuron lesions the signal path from the central nervous system to the muscles is interrupted. Functional electrical stimulation applied to the lower motor neurons can replace the lacking signals. A so-called neuroprosthesis may be used to restore motor function in paraplegic patients on the basis of functional electrical stimulation. However, the control of multiple joints is difficult due to the complexity, nonlinearity, and time-variance of the system involved. Furthermore, effects such as muscle fatigue, spasticity, and limited force in the stimulated muscle further complicate the control task. Mathematical models of the human musculoskeletal system can support the development of neuroprosthesis. In this article a detailed overview of the existing work in the literature is given and two examples developed by the author are presented that give an insight into model-based development of neuroprosthesis for paraplegic patients. It is shown that modelling the musculoskeletal system can provide better understanding of muscular force production and movement coordination principles. Models can also be used to design and test stimulation patterns and feedback control strategies. Additionally, model components can be implemented in a controller to improve control performance. Eventually, the use of musculoskeletal models for neuroprosthesis design may help to avoid internal disturbances such as fatigue and optimize muscular force output. Furthermore, better controller quality can be obtained than in previous empirical approaches. In addition, the number of experimental tests to be performed with human subjects can be reduced. It is concluded that mathematical models play an increasing role in the development of reliable closed-loop controlled, lower extremity neuroprostheses.

Applying fuzzy logic to control cycling movement induced by functional electrical stimulation

This study examines the design of a rational stimulation pattern for electrical stimulation and a robust closed-loop control scheme to improve cycling system efficacy for subjects with paraplegia. The stimulation patterns were designed by analyzing gravitation potential needed for the cycling movement of the lower limbs against a frictionless cycling ergometer and the response delay of electrically stimulated muscles. To simplify the cycling control system, the stimulation patterns were fixed and only the single gain of the stimulation patterns was adjusted via a feedback control algorithm. To circumvent the complexity involved with exactly modeling a stimulated muscle and cycling ergometer, a model-free fuzzy logic controller (FLC) was adopted herein for our control scheme. Comparison between FLC and conventional proportional-derivative (PD) controllers demonstrated that the FLC with asymmetrical membership function enabled the subject with paraplegia to maintain varied desired cycling speeds, particularly at lower cycling speed. By incorporating the rational stimulation patterns, the FLC can produce a smooth and prolonged cycling movement deemed necessary for designing various training protocols.

Cycle-to-cycle control of swing phase of paraplegic gait induced by surface electrical stimulation

Parameterised swing phase of gait in paraplegics was obtained using surface electrical stimulation of the hip flexors, hamstrings and quadriceps; the hip flexors were stimulated to obtain a desired hip angle range, the hamstrings to provide foot clearance in the forward swing, and the quadriceps to acquire knee extension at the end of the swing phase. We report on two main aspects; optimisation of the initial stimulation parameters, and parameter adaptation (control). The initial stimulation patterns were experimentally optimised in two paraplegic subjects using a controlled stand device, resulting in an initial satisfactory swinging motion in both subjects. Intersubject differences appeared in the mechanical output (torque joint) per muscle group. During a prolonged open-loop controlled trial with the optimised but unregulated stimulation onsets and burst duration for the three muscle groups, the hip angle range per cycle initially increased above the desired value and subsequently decreased below it. The mechanical performance of the hamstrings and quadriceps remained relatively unaffected. A cycle-to-cycle controller was then designed, operating on the basis of the hip angle ranges obtained in previous swings. This controller successfully adapted the burst duration of the hip flexors to maintain the desired hip angle range.

Nonlinear joint angle control for artificially stimulated muscle

Designs of both open- and closed-loop controllers of electrically stimulated muscle that explicitly depend on a nonlinear mathematical model of muscle input-output properties are presented and evaluated. The muscle model consists of three factors: a muscle activation dynamics factor, an angle-torque relationship factor, and an angular velocity torque relationship factor. These factors are multiplied to relate output torque to input stimulation and joint angle. An experimental method for the determination of the parameters of this model was designed, implemented, and evaluated. An open-loop nonlinear compensator, based upon this model, was tested in an animal model. Its performance in the control of joint angle in the presence of a known load was compared with a PID controller, and with a combination of the PID controller and the nonlinear compensator. The performance of the nonlinear compensator appeared to be strongly dependent on modeling errors. Its performance was roughly equivalent to that of the PID controller alone: somewhat better when the model was accurate, and somewhat worse when it was inaccurate. Combining the nonlinear open loop compensator with the PID feedback controller improved performance when the model was accurate.