**1. Introduction**

Computational Intelligence in Electromyography Analysis – 408 A Perspective on Current Applications and Future Challenges

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During the past decades, great effort has been devoted to devise new strategies for the control of artificial limbs fitted to patients with congenital defects or who have lost their limbs in accidents or surgery [1-6]. Most of that work was dedicated to minimize the great mental effort needed to control the prosthetic limb, especially during the first stages of training. When working with myoelectric prosthesis, that effort increases dramatically. These devices use EMG signals (the electrical manifestation of the neuromuscular activation associated with a contracting muscle) collected from remnant muscles to generate control inputs for the artificial limb. As these devices use a biological signal to control their movements, it is expected that they should be much easier to control. However, the prosthesis control is very unnatural and requires a great mental effort, especially during the first months after fitting [2, 7, 8]. As a result, a number of patients give up the use of those devices very soon. To overcome those problems, different techniques have been tried as an attempt to devise better strategies for myoelectric control.

This chapter describes the advent of Virtual Reality (VR) systems to create training environments dedicated to users of prosthetic devices. Those VR systems generally simulate a prosthesis that can react to commands issued by the users. A sophisticated system proposed by the authors is also described. Known as "*The Virtual Myoelectric Prosthesis*", the system is based on the use of EMG to control a virtual prosthesis in an Augmented Reality (AR) environment, in real time, providing the user with a more natural and intuitive training environment. The overall aim 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

© 2012 Barbosa Soares et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 Barbosa Soares et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

real one. Also, the research team believes that, since real upper limb prostheses are relatively heavy and 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 metal effort usually necessary, especially in the first trials.

Virtual and Augmented Reality: A New Approach to Aid Users of Myoelectric Prostheses 411

during the first trimester of pregnancy, has killed thousands of babies. Those who survived experienced birth defects such as deafness, blindness, disfigurement, and especially the shortening or absence of members. Responding to this tragedy, several research centers intensified the efforts towards the design of artificial limbs as an attempt to improve the

Also, during that period, russian scientists had introduced a prosthetic hand controlled by a signal generated by the activity of remaining muscles from amputated limbs [8]. That type of control has been described as "myoelectric control" and the prosthesis, by extension, has

The control of prostheses can be considered one of the most interesting challenges related to prosthetics. Ideally, a prosthetic limb should be controlled without any effort from the user,

Currently, there are two main strategies for controlling artificial limbs: biomechanical and bioelectrical. In the first, the motion of parts of the body results in the activation of the limb, whereas, in the latter, biosignals, generated from the electrical activity of muscles, are detected and interpreted in order to generate commands for controlling the prosthesis. Nevertheless, there is ongoing research seeking other forms of control based on more natural strategies, such as those that employ brain or neuronal activity together with

As described earlier, the first prostheses were generally passive devices that relied on intact parts of the body for their positioning and controlling. This extremely successful design allowed the user to control the device so that the movement of a part of the body was reflected in movements of parts of the prosthesis. Despite some modifications, this design remains basically the same nowadays, being the most popular control mechanism among users [10]. The reasons for such success are not well established, but according to Doeringer and Hogan [15] some of the key factors are: it results in a relatively inexpensive prosthesis; the final prosthesis is not too heavy; after training, the user begins to use the prosthesis as a natural extension of his body, having, for example, the notion of weight and size of the prosthetic limb. Kruit and Cool [16] described the main drawbacks: the mechanism of harnesses used to propagate the movements of the body is usually uncomfortable; the movement of the prosthesis requires significantly large forces; the number of control inputs

is limited and thus the number of degrees of freedom of the prosthesis is also limited.

An alternative to the Body-Powered control is to employ the myoelectric control, which uses the electrical activity of muscle contraction (electromyographic signal) as a primary source of control. The prostheses that use this type of control typically do not require cables and, in some situations, there is no need for suspension straps. The operation of a myoelectric device can be summarized as follows: the brain sends commands, i.e., neuronal impulses that travel through nerves and reach the endplate of a given muscle, which, in turn, causes

lives of those children.

**2.1. Controlling strategies** 

sensory feedback [5-7, 12-14].

been described as "myoelectric prosthesis".

similar to the subconscious control of a natural limb.
