Muscle force augmentation by low-intensity electrical stimulation

Human-FES Cooperative Control for Wrist Movement: A Preliminary Study

Functional electrical stimulation (FES) sometimes applies to patients with partial paralysis, so human voluntary control and FES control both exist. Our study aims to build a cooperative controller to achieve human-FES cooperation. This cooperative controller is formed by a classical FES controller and an impedance controller. The FES controller consists of a back propagation (BP) neural network-based feedforward controller and a PID-based feedback controller. The function of impedance controller is to convert volitional force/torque, which is estimated from a three-stage filter based on EMG, into additional angle. The additional angle can reduce the FES intensity in our cooperative controller, comparing to that in classical FES controller. Some assessment experiments are designed to test the performance of the cooperative controller.

A phenomenological model that predicts forces generated when electrical stimulation is superimposed on submaximal volitional contractions

Superimposition of electrical stimulation during voluntary contractions is used to produce functional movements in individuals with central nervous system impairment, to evaluate the ability to activate a muscle, to characterize the nature of fatigue, and to improve muscle strength during postsurgical rehabilitation. Currently, the manner in which voluntary contractions and electrically elicited forces summate is not well understood. The objective of the present study is to develop a model that predicts the forces obtained when electrical stimulation is superimposed on a volitional contraction. Quadriceps femoris muscles of 12 able-bodied subjects were tested. Our results showed that the total force produced when electrical stimulation was superimposed during a volitional contraction could be modeled by the equation T=V+S[(MaxForce-V)/MaxForce]N, where T is the total force produced, V is the force in response to volitional contraction alone, S is the force response to the electrical stimulation alone, MaxForce is the maximum force-generating ability of the muscle, and N is a parameter that we posit depends on the differences in the motor unit recruitment order and firing rates between volitional and electrically elicited contractions. In addition, our results showed that the model predicted accurately (intraclass correlation coefficient>or=0.97) the total force in response to a wide range of stimulation intensities and frequencies superimposed on a wide range of volitional contraction levels. Thus the model will be helpful to clinicians and scientists to predict the amount of stimulation needed to produce the targeted force levels in individuals with partial paralysis.