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, we further evaluated the performance 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.

Model-based control of FES-induced single joint movements

The goal of this study was to design a robot system for assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The robot should be able to guide patient's wrist to move along planned linear or circular trajectories. A hybrid position/force controller incorporating fuzzy logic was developed to constrain the movement in the desired direction and to maintain a constant force along the moving direction. The controller was stable in the application range of movements and forces. Offline analyses of data were used to quantitatively assess the progress of rehabilitation. The results show that the robot could guide the upper limbs of subjects in linear and circular movements under predefined external force levels and apply a desired force along the tangential direction of the movements.

A rehabilitation robot with force-position hybrid fuzzy controller: hybrid fuzzy control of rehabilitation robot

Brunnstrom’s Clinical Kinesiology

Purpose. To assess the change in bone mineral density (BMD) after spinal cord injury (SCI) and to evaluate whether BMD loss can be reversed with the intervention of functional electric stimulation cycling exercises (FESCE).Methods. Fifteen males with SCI were included. Fifteen able-bodied males were also tested to compare BMD. In the SCI group, the FESCE was performed for six months, and then was discontinued in the subsequent six months. BMD was performed before the FESCE, immediately after six months of the FESCE, and at the end of the subsequent six months.Results. Before the FESCE, the BMD of the SCI subjects in every site, except the lumbar spine, was lower than that of the able-bodied subjects. After six months of FESCE, BMD of the distal femur (DF) and proximal tibia (PT) increased significantly, and BMD of the calcaneus (heel) showed a trend of increase. However, the BMD in the DF, PT, and heel decreased significantly after the subsequent six months without FESCE. The BMD of the femoral neck (FN) ...

Increases in bone mineral density after functional electrical stimulation cycling exercises in spinal cord injured patients

The feedback error learning (FEL) scheme was studied for a functional electrical stimulation (FES) controller. This FEL controller was a hybrid regulator with a feedforward and a feedback controller. The feedforward controller learned the inverse dynamics of a controlled object from feedback controller outputs while control. A four-layered neural network and the proportional-integral-derivative (PID) controller were used for each controller. The palmar/dorsi-flexion angle of the wrist was controlled in both computer simulation and FES experiments. Some controller parameters, such as the learning speed coefficient and the number of neurons, were determined in simulation using an artificial forward model of the wrist. The forward model was prepared by using a neural network that can imitate responses of subject's wrist to electrical stimulation. Then, six able-bodied subjects' wrist was controlled with the FEL controller by delivering stimuli to one antagonistic muscle pair. Results showed that the FEL controller functioned as expected and performed better than the conventional PID controller adjusted by the Chien, Hrones and Reswick method for a fast movement with the cycle period of 2 s, resulting in decrease of the average tracking error and shortened delay in the response. Furthermore, learning iteration was shortened if the feedforward controller had been trained in advance with the artificial forward model.

Joint angle control by FES using a feedback error learning controller

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 the authors' control scheme. Comparison between FLC and conventional proportional-derivative (PD) controllers demonstrated that the PLC 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.

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

The fatigue characteristics of paralyzed muscles were investigated during dynamic cycling movement induced by functional electrical stimulation (FES). The peak-to-peak (PTP) amplitude of stimulus-evoked electromyogram (EMG), after suppression of stimulus artifact, was adopted as fatigue indicator. Compared to static contraction, the effects of dynamic movement factors on the stimulus-evoked EMG, such as the intermittent stimulation, joint angle, and contraction speed, were first evaluated in separate experiments. The results of isolated tests laid the foundation for interpreting the data obtained in two FES-cycling experiments, performed under maximum stimulation or in controlled cycling speeds. The effects of intermittent stimulation and joint angle caused periodic changes in PTP amplitude which can be alleviated by averaging the PTP amplitude of one cycle. Under the same stimulation intensity, the authors' results indicated that slower muscle contraction speed would have larger PTP amplitude and vice versa. For the limited number of subjects with paraplegia studied, the authors' results showed that the use of EMG PTP as reliable muscle fatigue indicator during dynamic movement is only valid at the same cycling speed or corresponding contraction speed. The decline of the PTP amplitude decreased with the decay of muscle force can be observed during cycling movement; however, reduction of cycling speed had the opposite effect on PTP amplitude. Observations from the hyperbolic modeling of fatigue process demonstrated that the EMG PTP of a fatigued muscle under dynamic movement decreased at a slower rate.

The validity of stimulus-evoked EMG for studying muscle fatigue characteristics of paraplegic subjects during dynamic cycling movement

This study compared the different fatigue processes of electrically elicited static and dynamic muscle contractions of quadriceps in five paraplegic subjects. An electrodynamometer was utilized for recording the generated torque output and controlling the isokinetic dynamic movements. Stimulus-evoked electromyography (EMG), after artifact suppression, was used to observe the fatigue process. Besides torque output, the measured EMG features included peak to peak amplitude, rise time to peak and peak to peak duration. The measurements were modeled by a hyperbolic tangent function, which allowed observance of their time constants, inflection times and relative residual levels during the fatigue process. The time constants as well as the inflection time of torque output and EMG features were compared between static and dynamic contractions. The inflection times of torque output and all EMG features measured during static contraction were found larger than those of dynamic contraction. In EMG temporal features, the inflection times of rise time to peak and peak to peak duration in static contractions were also found significantly larger than those of dynamic contractions. These conditions indicated that, from either contractile (torque curves) or excitation (EMG features) aspects, the electrically elicited muscle contraction in dynamic movement is prone to fatigue earlier and faster.

/pdf/study-of-the-electrically-evoked-emg-and-torque-output-5f7oqjco74.pdf

Study of the electrically evoked EMG and torque output during the muscle fatigue process in FES-induced static and dynamic contractions

The muscle fatigue characteristics was studied from biomechanical modelling analysis and stimulus EMG measurement during FES-induced cycling movement. The inverse dynamics method was used to calculate the knee joint torque which represents the muscle force generated during cycling movement. The peak-to-peak of stimulus EMG, after suppression of stimulus artifact, was adopted as a fatigue indicator during dynamic movement. Our observations from stimulus EMG and inverse dynamics indicate that the paralyzed muscles might not reach complete fatigue when the cycling movement cannot continue.

Nan-Ying Yu

Papers

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

The validity of stimulus-evoked EMG for studying muscle fatigue characteristics of paraplegic subjects during dynamic cycling movement

Study of the electrically evoked EMG and torque output during the muscle fatigue process in FES-induced static and dynamic contractions

Muscle fatigue study in FES-induced dynamic cycling movement