Abstract
This article proposes the use of Augmented Reality (AR) techniques for control and simulation of myoelectric prostheses. The system has been designed so that it is able to reproduce the operation of a real prosthesis in an immersive AR environment, using a virtual device that operates in similar fashion to the real one, resulting in a training environment for users and therapists. Motion and posture of the virtual prosthesis is controlled by EMG signals collected via surface electrodes and classified into four classes of movements. The results of tests with non-amputee volunteers show that the system is capable of generating the correct prosthesis motion and posture in the AR environment, in real time.
Highlights
This article proposes the use of Augmented Reality (AR) as an aiding tool for the helping patients to operate and properly control myoelectric upper limb prostheses
The overall aim of this work is to reproduce the operation of a real prosthesis in an immersive AR environment, using a virtual device that operates in similar fashion to the real one, resulting in a training environment for users and therapists
A very popular approach for prosthesis control is based on the use of EMG signals, collected from remnant muscles, to generate control inputs
Summary
This article proposes the use of Augmented Reality (AR) as an aiding tool for the helping patients to operate and properly control myoelectric upper limb prostheses. Since real upper limb prostheses are relatively heavy and it can become uncomfortable and cumbersome, especially during the first stages of fitting, the use of a virtually weightless and fully controllable device can help reducing the great physical and mental effort usually necessary, especially in the first trials. A very popular approach for prosthesis control is based on the use of EMG signals (the electrical manifestation of the neuromuscular activation associated with a contracting muscle), collected from remnant muscles, to generate control inputs. Since those devices, known as myolectric prostheses, use a biological signal to control their movements, it is expected that they should be much easier to operate. It is important to devise new strategies for control and for training new users
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