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.

A multichannel functional electrical stimulation (FES) system for the restoration of quadriplegic upper extremity function is described. The system is composed of a personal computer NEC PC-8801mkII, peripheral electronic circuits, CRT display and respiratory sensors for volitional control by the patient, and percutaneous electrodes. A C4 quadriplegic patient could drink canned tea by herself by using this FES system. Distinct features of the system are as follows: 1) Versatile volitional control was realized by controlling the memory allocation of the stored stimulation data by voluntary respiratory signals. 2) Sophisticated fine control of the fingers, wrists, and elbow was realized by creating the multichannel stimulation data from recorded myoelectric activities of normal subjects during movements of the upper limb.

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In basic experiments employing silicone rubber tubes with nonuniform wall thickness as arterial models, the elastic moduli of silicone rubber tubes were evaluated by measuring changes in wall thickness. These results confirm the value of the proposed method.

SUMMARYIn restoring motor functions of paralyzed extremities by functional electrical stimulation (FES), determination of stimulus intensities of many muscles in multichannel control is an ill-posed problem because of redundancy in the input (stimulus intensity)-output (joint angle) relationship of the musculoskeletal system. In this paper, we use a multi-input and multi-output PID controller and propose a parameter determination method for the controller, which can solve the ill-posed problem in closed-loop control. In the parameter determination process, the stimulus intensity-joint angle characteristics of all muscles controlled were measured first. The elements of the matrix that transforms stimulus intensities into joint angles were determined by linear approximation of the measured characteristics. Then a generalized inverse matrix of the transformation matrix was calculated. The generalized inverse matrix and an expanded CHR method were used to determine the parameters of the PID controller. The PID controller was examined in tracking control on several trajectories of two-degree-of-freedom movement of the wrist joint with neurologically intact subjects. Electrical stimulation was applied to four muscles relating to the wrist joint movements through surface electrodes. The tracking control was achieved generally with good performance under different conditions of the gravitational effect. The new method proposed in this paper was found to provide a solution of the ill-posed problem. Multichannel closed-loop FES control of the wrist joint could be realized with this method.