No abstract

No abstract

No abstract

Abstract-In this paper design of a closed loop FES system for torque control is presented. Snap power worker s used for measuring muscle torque. Using this system torque is proportional to angle of a flexion so by controlling angle of a flexion torque is controlled too. During functional electrical stimulation 3 parameters can be changed: pulse width, pulse amplitude and time between two impulses. In this paper pulse amplitude and frequency are constant and system is controlled by changing pulse width. PI regulator is used to minimize difference between desired trajectory and system output. Parameters of a PI controller are obtained by minimizing mean square error on simulated system. In this paper NARX Radial based neural network model of system is used for simulation. Result on a real system show that this type of control system can be used for torque control.

Electromyography (EMG) is a well known technique used for recording electrical activity produced by human muscles. In the last few decades, EMG signals are used as a control input for prosthetic hands. There are several multifunctional myoelectric prosthetic hands for amputees on the market, but so forth, none of these devices permits the natural control of more than two degrees of freedom. In this paper we present our implementation of the pattern classification using custom made components (electrodes and an embedded EMG amplifier). The components were evaluated in offline and online tests, in able bodied as well as amputee subjects. This type of control is based on computing the time domain features of the EMG signals recorded from the forearm and using these features as input for a Linear Discriminant Analysis (LDA) classifier estimating the intention of the prosthetic user.