**1. Introduction**

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268 Electrodiagnosis in New Frontiers of Clinical Research

Three types of prosthetic hand are currently available: cosmetic, body-powered, and myoelectric (Laschi *et al.*, 2000). Cosmetic prostheses are passive, and designed to look like the natural hand, with solely an aesthetic purpose. Body-powered prostheses are pow‐ ered and controlled by body movements, generally of the shoulder or of the back. Myoelectric hands are electrically powered and controlled by electromyographic (EMG) signals; *i.e.*, small electric potentials produced by contracting muscles. Myoelectric hands are typically controlled in switched or simple proportional mode, according to the amplitude of the EMG signals (Stein and Walley, 1983; Näder, 1990; Sears and Shaper‐ man, 1991; Bergman *et al*., 1992; Kyberd and Chappell, 1994). The switched control is the simplest one, as it consists of only two states: on or off. Although much progress has been made in myoelectric hands, their motor functions are still not comparable with those of a natural hand, partly because they have been designed to provide only the most basic functions of a natural hand, such as grasping and holding.

Akazawa's Lab has developed a myoelectric prosthetic hand (*Osaka Hand*) that simulates fundamental dynamic properties of the neuromuscular control system of the human hand, mainly the viscoelastic properties of muscles, which depend on their stiffness (Akazawa *et al*., 1987). This hand can be used by an amputee subject with almost the same subconscious control that he/she had prior amputation (Okuno *et al*., 1999).

The current design of the *Osaka Hand* requires the user to be fitted for and to wear a handmade fiberglass or thermoplastic socket into which the stump is comfortably and tightly

© 2013 García et al.; licensee InTech. This is an open access article 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. © 2013 García 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.

inserted. The *Osaka Hand* is attached to the other tip of the socket via a screw. This socket is expensive to produce and requires weeks to manufacture after measurements are taken (Sears, 1991).

location for the EMG signals acquisition in each individual. In addition, the simulator allows physicians and related staff to recognize how easily the hand can be controlled and its

Simulator of a Myoelectrically Controlled Prosthetic Hand with Graphical Display of Upper Limb and Hand Posture

The simulator that we have developed consists of a data acquisition system, a mathematical model that simulated the behavior of the *Osaka Hand* (including its model of the human

A general overview of the system is shown in Figure 1. An exceptional feature of the *Osaka Hand* is that the user can control voluntarily the angle of its fingers and the stiffness of the grip (the resistance that the fingers oppose to change their angle) by the EMGs of flexor and extensor

To obtain such a control, the *Osaka Hand* mimics the properties of both muscle viscoelastic‐ ity and the gain of the stretch reflex (both varying linearly with muscle activity). The dynamics of this neuromuscular control system were determined by analyzing the tension responses of finger muscle to mechanical stretch (Akazawa *et al.*, 1999). The dynamics are quite complex, due to the non-linearity and time delay of the stretch reflex; however, we used a simple model representing the dynamics as a first approximation. Once that model was introduced in the prosthetic hand, it was proved that a sound-limbed subject and an amputee subject were able to accurately control finger angle and stiffness of the prosthet‐

As shown in Figure 1, for each subject a pair of surface electrodes were put on the *flexor carpi radialis* (wrist flexor muscle) and another pair on their *extensor carpi radialis brevi* (wrist extensor muscle) to measure their EMG signal. The measured signal was amplified in differential mode, full-wave rectified, and then smoothed with a low-pass filter to obtain its envelope, the amplitude of which is approximately proportional to the force exerted by the muscle (Basmajian and Deluca, 1985). Therefore, the resultant signal corresponded to the isometric contractile force (torque) of each muscle: *Af* being the torque of the flexor muscle, and *Ae* the

where *PH* is the grip force exerted by the fingers of the *Osaka Hand*, and was measured by strain gauges (KYOWADENGYOCo.,Ltd.(Yokohama,Japan),modelKFG-1N)attachedtoits thumb,

( ) { ( ) ( ) ( )} / ( ) *H Hef x* Q= + - *s P s As A s Gs* % (1)

*<sup>H</sup>* of the end effector (the target

http://dx.doi.org/10.5772/55503

271

neuromuscular control system dynamics), and a graphics display device.

advantages over other kinds of prosthesis.

**2. Materials and methods**

**2.1. Structure of the** *Osaka Hand*

ic hand (Okuno *et al.*, 1999).

torque of the extensor muscle.

muscles of the wrist (see details in Akazawa *et al.*, 1987).

From those two calculated torques, the desired finger angle *<sup>Θ</sup>*˜

angle the user wants to achieve) was calculated as

An additional initial problem is that shortly after an amputation atrophy of the remnant muscles occurs, and their EMG signal becomes very weak. As that EMG signals are used to control the prosthesis, users wanting to wear the *Osaka Hand* (or any other myoelectric hand) must undergo a training phase in which their remnant muscles are strengthened and at the same time they re-learn how to perform fine, detailed muscles contractions, which are needed for a precise control of the prosthetic hand.

In order to solve the two problems mentioned above, we developed a graphic simulator system for the *Osaka Hand* that eliminates the need of a socket for attachment of that prosthetic hand to the stump and it is also used for physical training of myoelectric patients.

A number of works on prosthesis simulators have been already described, each of them fitting the specific requirements of a given prosthesis. Yamada *et al.* (1983) employed six different bidimensional (2D), fix images appearing on the screen depending on the frequency and amplitude pattern of three EMG signals in order to evaluate their proposed control method for a theoretical prosthetic hand. Daley *et al.* (1990) developed a simple 2D graphical simulator for operator performance comparison when using different myoelectric control strategies. Abul-Haj and Hogan (1987) performed an emulation with a combination of software and hardware for elbow-prosthesis prototypes evaluation. Perlin *et al.* (1989) developed a simula‐ tion program for their Utah/MIT 16-joint, four-finger *Dextrous Hand*.

Several works describe simulators operated by shoulder movement; Zahedi and Farahani (1995), for example, used a graphical simulator for a fuzzy EMG classifier; Durfee *et al.* (1991) created a 2D graphic simulator to evaluate command channels trough which control an upper limb neural prosthesis; and Zafar and Van Doren (2000) employed a videobased simulator for a shoulder-activated neuroprosthesis for spinal cord injured persons. Lin and Huang (1997) made a computer simulation of a robotic hand to test its potential use as a prosthesis.

There are already some commercially available systems such as *MyoBoy* –from OTTO BOCK HealthCare GmbH (Duderstadt, Germany)- that is a software tool used for the evaluation, selection, training, and documentation of myoelectric patients. MOTION CONTROL Inc. (Utah, USA) has developed an EMG tester and trainer (*Myolab II*) that is used to locate intact muscle activity and to help patients in strengthening and relaxation tasks.

However, all the abovementioned simulators can be used only with prosthetic hands with a switched or single proportional mode, not for those with a more complex control mode as the one of the *Osaka Hand*.

The goal of the present work was to develop an upper limb and hand graphic simulator system that solves the abovementioned problems, allowing amputee subjects to try virtually the myoelectric hand without needing the socket, and to perform the physical training required prior to use the real one. This simulator allows us also to easily identify the optimal electrode location for the EMG signals acquisition in each individual. In addition, the simulator allows physicians and related staff to recognize how easily the hand can be controlled and its advantages over other kinds of prosthesis.

The simulator that we have developed consists of a data acquisition system, a mathematical model that simulated the behavior of the *Osaka Hand* (including its model of the human neuromuscular control system dynamics), and a graphics display device.
