**Acknowledgements**

To measure how accurately the subjects performed the task, we calculated the mean square

where *ΘHS n* is the hand simulator finger angle in the sample *n*, and *N* is the number of

An additional control experiment was carried out to examine whether the subjects were able to grasp a virtual object using the simulator hand. In this grasping control task, six spheres with different diameters (from 2 mm to 10 cm) were depicted one at a time on a fix position on the simulator screen. The subject was instructed to grasp them with the virtual hand. To give some feedback to the subjects about the virtual force exerted over the sphere, a second index finger was drawn (with a very faint color) in the position the simulated index finger

The results of this experiment were very similar to the ones shown in Figure 8. In this case, we defined the error as the distance between the index fingertip and the surface of the sphere. The average error while subjects tried to hold onto the sphere in the last two trails of each subject was 1.32 mm (s.d. 0.47). For the amputee subject, the average error was 1.77 mm (s.d. 0.63). In conclusion, subjects were able to grasp the object, and to do it in a smooth, natural way. These results prove that the simulator developed in this work is a valid tool for rehabilitation.

In this study, we have introduced a simulator of our biomimetic, myoelectric prosthetic hand (*Osaka Hand*), which is operated by the subject's EMG signals, and displays in 3D a virtual arm

We have demonstrated that the simulator output agrees sufficiently for practical use with the

Usefulness of the simulator has been shown in the experiments of controlling angle and stiffness of the hand. After a short period of training, subjects were able to control quite accurately the simulated hand. The precision achieved by an amputee subject was nearly as good as the precision obtained by the three non-amputee subjects, even though the amputee

finger angle of the prosthetic hand when both are given the same input.

had not actively used his forearm muscles for four years.

(*ΘHS n* −*Θtarget*)<sup>2</sup> (5)

(s.d. 0.67) for the three non-amputee subjects and 1.78o

as the acceptable range of error (dashed

error *ε* made while trying to keep a constant target angle *Θtarget* as

*<sup>ε</sup>* <sup>=</sup> <sup>1</sup> *<sup>N</sup>* ∑ *n*=1 *N*

samples between the points *A* and *B*. We defined ±2o

would have been if there was not a solid object in its way.

horizontal lines in Figure 8).

*3.2.2. Grasping control*

**4. Conclusion**

and a prosthetic hand.

(s.d. 0.54o

The average of the error *ε* was 1.19o

282 Electrodiagnosis in New Frontiers of Clinical Research

) for the amputee subject.

This work was partially funded by the Ministry of Education, Culture, Sports, Science, and Technology of Japan. G.A.G. was funded by a grant from the same Ministry (*Monbusho*). This work was carried out at Akazawa's Laboratory, Graduate School of Information Science and Technology, Osaka University (Osaka, Japan).

G.A.G. thanks Professor Pedro García Teodoro (Granada University, Granada, Spain) for encouragement and scientific support during the first stages of this project.

Authors would like to thank as well Dr. Sandra Rainieri (AZTI Foundation, Bilbao, Spain) and Professor Antonio Peinado (Granada University, Granada, Spain) for useful comments and input on the original manuscript.
