ABSTRACT
This paper describes the development of a low-cost hand prosthesis for use in patients with an amputated hand due to congenital problems or to trauma wound, who possess a part or the forearm endowed with muscular activity. The paper covers the constructive aspects of both mechanical and electronic designs. The prototype is controlled by electromyographic signals measured at the remaining part of the injured limb of the patient. The EMG signals are measured at the surface of the skin, at a point that is close to a working muscle of the amputated arm. The prosthesis allows the patient to hold objects by means of a three finger clamp. The prosthesis presented an excellent performance in preliminary tests with an amputated patient. These tests showed that the prosthesis had a very good performance regarding force and speed.
Subject(s)
Artificial Limbs , Electromyography/methods , Hand , Movement/physiology , Muscle Contraction/physiology , Robotics/instrumentation , Action Potentials/physiology , Amputees/rehabilitation , Artificial Intelligence , Biomechanical Phenomena/instrumentation , Electric Power Supplies , Electromyography/instrumentation , Equipment Design , Equipment Failure Analysis , Feedback , Humans , Prosthesis Design , Therapy, Computer-Assisted/methodsABSTRACT
The operation of an optoelectronic dynamic neural model implementation is extended to higher frequencies. A simplified model of thermal effects in vertical-cavity surface-emitting lasers correctly predicts the qualitative changes in the nonlinear mapping implementation with frequency. Experiments and simulations show the expected resonance properties of this model neuron, along with the possibility of other dynamic effects in addition to the ones observed in the original FitzHugh-Nagumo equations. Results of optical coupling between two similar pulsing artificial neurons are also presented.
ABSTRACT
An optoelectronic implementation of a modified FitzHugh-Nagumo neuron model is proposed, analyzed, and experimentally demonstrated. The setup uses linear optics and linear electronics for implementing an optical wavelength-domain nonlinearity. The system attains instability through a bifurcation mechanism present in a class of neuron models, a fact that is shown analytically. The implementation exhibits basic features of neural dynamics including threshold, production of short pulses (or spikes), and refractoriness.
