Functional Electrical Stimulation (FES) can be effective in assisting or restoring paralyzed motor functions. The purpose of this study is to examine experimentally the fuzzy controller based on cycle-to-cycle control for FES-induced gait. A basic experimental test was performed on controlling maximum knee extension angle with normal subjects. In most of control trials, the joint angle was controlled well compensating changes in muscle responses to electrical stimulation. The results show that the fuzzy controller would be practical in clinical applications of gait control by FES. An automatic parameter tuning would be required practically for quick responses in reaching the target and in compensating the change in muscle responses without causing oscillating responses.

The purpose of this study was to develop a practical functional electrical stimulation (FES) controller for joint movements restoration based on an optimal control technique by cascading a linear model predictive control (MPC) and a nonlinear transformation. The cascading configuration was aimed to obtain an FES controller that is able to deal with a nonlinear system. The nonlinear transformation was utilized to transform the linear solution of linear MPC to become a nonlinear solution in form of optimized electrical stimulation intensity. Four different types of nonlinear functions were used to realize the nonlinear transformation. A simple parameter estimation to determine the value of the nonlinear transformation parameter was also developed. The tracking control capability of the proposed controller along with the parameter estimation was examined in controlling the 1-DOF wrist joint movement through computer simulation. The proposed controller was also compared with a fuzzy FES controller. The proposed MPC-FES controller with estimated parameter value worked properly and had a better control accuracy than the fuzzy controller. The parameter estimation was suggested to be useful and effective in practical FES control applications to reduce the time-consuming of determining the parameter value of the proposed controller.

The fuzzy controller based on cycle-to-cycle control with output value adjustment factors (OAF) was developed for restoring gait of paralyzed subjects by using functional electrical stimulation (FES). Results of maximum knee flexion and extension controls with neurologically intact subjects suggested that the OAFs would be effective in reaching the target within small number of cycles and in reducing the error after reaching the target. Oscillating responses between cycles were also suppressed. The fuzzy controller was expected to be examined to optimize the OAFs with more subjects including paralyzed patients for clinical application.

The goal of this study was to design a practical fuzzy controller of the cycle-to-cycle control for multi-joint movements of swing phase of functional electrical stimulation (FES) induced gait. First, we designed three fuzzy controllers (a fixed fuzzy controller, a fuzzy controller with parameter adjustment based on the gradient descent method, and a fuzzy controller with parameter adjustment based on a fuzzy model) and two PID controllers (a fixed PID and an adaptive PID controllers) for controlling two-joint (knee and ankle) movements. Control capabilities of the designed controllers were tested in automatic generation of stimulation burst duration and in compensation of muscle fatigue through computer simulations using a musculo-skeletal model. The fuzzy controllers showed better responses than the PID controllers in the both control capabilities. The parameter adjustment based on the fuzzy model was shown to be effective when oscillating response was caused due to the inter-subject variability. Based on these results, we designed the fuzzy controller with the parameter adjustment realized using the fuzzy model for controlling three-joint (hip, knee, and ankle) movements. The controlled gait pattern obtained by computer simulation was not significantly different from the normal gait pattern and it could be qualitatively accepted in clinical FES gait control. The fuzzy controller designed for the cycle-to-cycle control for multi-joint movements during the swing phase of the FES gait was expected to be examined clinically.

We proposed a fuzzy control scheme to implement the cycle-to-cycle control for restoring swing phase of gait using functional electrical stimulation (FES). We designed two fuzzy controllers for the biceps femoris short head (BFS) and the vastus muscles to control flexion and extension of the knee joint during the swing phase. Control capabilities of the designed fuzzy controllers were tested and compared to proportional-integral-derivative (PID) and adaptive PID controllers in automatic generation of stimulation burst duration and compensation of muscle fatigue through computer simulations using a musculo-skeletal model. Parameter adaptations in the adaptive PID controllers did not significantly improve the control performance of the PID controllers. The fuzzy controllers were superior to the PID and adaptive PID controllers under several subject conditions and different fatigue levels. These results showed the fuzzy controller would be suitable to implement the cycle-to-cycle control of FES-induced gait.