*3.1.2. Variable stiffness*

As one of the main features of the *Osaka Hand* is that the subject can control its stiffness by antagonist muscles co-contraction, we performed another experiment to corroborate that the stiffness of the virtual hand fingers can be controlled in that same way.

To simulate different levels of co-contraction, we fed the simulator with different levels of *Ae* and *Af* under the condition (*Ae* = *Af* ) (see Figure 3(b) and (c1)). We sinusoidally modulated the

*3.1.3. Effect of force feedback*

angle was around 43o

was 3o

when *PHS* was calculated as explained above.

We carried out a preliminary experiment to study the simulator behavior when a subject grasped a virtual object (a sphere). The mechanical dynamics of the object were modeled in a

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

where *Ks* is the spring constant; *ΘHS* 0 is the finger angle when the contact with the object occurs, and *ΘHS* is the current angle. The inputs *Ae* and *Af* to the simulator were given as sinusoidal waves. Figure 7(a) compares the fingers angle when grasping the sphere: continuous line curve corresponds to the experiment carried out without *PHS* feedback; and the dashed line curve

The first contact fingers-sphere occurred at *t* =9.5*s* (marked in the graph as A), when the fingers

**Figure 6.** Stiffness (resistance to perturbations) control experiment. In response to the same simulated perturbation, an increase of co-contraction level decreases the amplitude of the perturbation effect (increase of the stiffness).

feedback, practically the third part of the whole simulated fingers angle range (110 o).

. Therefore, there is a difference of approximately 40o in *ΘHS* providing or not *PHS*

. The maximal grasping force occurs when the fingers angle without *PHS*

*PHS* = *Ks* ⋅ (*ΘHS* −*ΘHS* 0) (4)

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

279

simple fashion as a spring (Figure 3(c4)). The exerted force *PHS* was calculated then as

**Figure 5.** Comparison between simulator and actual *Osaka Hand* finger angles. (a) Same inputs given to both the sim‐ ulator and the prosthetic hand. (b) Simulator output (thin line) and prosthesis actual finger angle (thick line).

applied grip force *PHS* (see Figure 3(c4)) at a frequency of 0.2 Hz and a range between -0.08 V and 0.08 V, which corresponds to the actual output amplitude of the strain gauges. Figure 6 shows that as *Ae* + *Af* increased –that is, as the level of co-contraction increased-, in response to the same perturbation *PHS* , the finger angle displacement decreased; that is, the stiffness increased. When there was no co-contraction (*Ae* + *Af* = 0V), the perturbation caused the total opening of the hand (110o is its maximal aperture), but when the level of co-contraction was maximum (*Ae* + *Af* = 10V), the perturbation had nearly no effect on the angle of the hand fingers. Therefore, the simulator behaves like the *Osaka Hand* also in stiffness.

### *3.1.3. Effect of force feedback*

applied grip force *PHS* (see Figure 3(c4)) at a frequency of 0.2 Hz and a range between -0.08 V and 0.08 V, which corresponds to the actual output amplitude of the strain gauges. Figure 6 shows that as *Ae* + *Af* increased –that is, as the level of co-contraction increased-, in response to the same perturbation *PHS* , the finger angle displacement decreased; that is, the stiffness increased. When there was no co-contraction (*Ae* + *Af* = 0V), the perturbation caused the total opening of the hand (110o is its maximal aperture), but when the level of co-contraction was maximum (*Ae* + *Af* = 10V), the perturbation had nearly no effect on the angle of the hand

**Figure 5.** Comparison between simulator and actual *Osaka Hand* finger angles. (a) Same inputs given to both the sim‐ ulator and the prosthetic hand. (b) Simulator output (thin line) and prosthesis actual finger angle (thick line).

fingers. Therefore, the simulator behaves like the *Osaka Hand* also in stiffness.

278 Electrodiagnosis in New Frontiers of Clinical Research

We carried out a preliminary experiment to study the simulator behavior when a subject grasped a virtual object (a sphere). The mechanical dynamics of the object were modeled in a simple fashion as a spring (Figure 3(c4)). The exerted force *PHS* was calculated then as

$$P\_{HS} = \mathcal{K}\_s \cdot \left(\Theta\_{HS} - \Theta\_{HS0}\right) \tag{4}$$

where *Ks* is the spring constant; *ΘHS* 0 is the finger angle when the contact with the object occurs, and *ΘHS* is the current angle. The inputs *Ae* and *Af* to the simulator were given as sinusoidal waves. Figure 7(a) compares the fingers angle when grasping the sphere: continuous line curve corresponds to the experiment carried out without *PHS* feedback; and the dashed line curve when *PHS* was calculated as explained above.

The first contact fingers-sphere occurred at *t* =9.5*s* (marked in the graph as A), when the fingers angle was around 43o . The maximal grasping force occurs when the fingers angle without *PHS* was 3o . Therefore, there is a difference of approximately 40o in *ΘHS* providing or not *PHS* feedback, practically the third part of the whole simulated fingers angle range (110 o).

**Figure 6.** Stiffness (resistance to perturbations) control experiment. In response to the same simulated perturbation, an increase of co-contraction level decreases the amplitude of the perturbation effect (increase of the stiffness).

Figure 7(*b*) shows the value of the calculated *PHS* . When it reaches its maximal value, approx‐ imately 25 mV (roughly one third of its maximum), the difference between the fingers target angle with and without pressure feedback is nearly 10o . Therefore, as it happens with the real prosthetic hand (Okuno *et al.*, 1999), *PHS* gives self-control to the hand over the exerted force when grasping objects, producing a smoother grasping motion.

comparing the performance of the subjects before and after two trails. In this finger angle

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

Figure 8 shows the typical results obtained, where the target angle to achieve was 55o (thick horizontal line). Figures 8(a) and 8(c) (left column) show the results of the first trial of two different subjects; (a) a sound-limbed subject and (c) the amputee subject. Both subjects needed more than 4 s to be able to keep the angle within the acceptable range, and were able to maintain

Figure 8(b) shows the results obtained by the sound-limbed subject after several trials for a period of about 40 min, and Figure 8(d) for the amputee subject after a similar period. In this case, both achieved the angle in just approximately 1 s (point *A*), and held it until they were

**Figure 8.** Effect of training on position control (step response). The target angle was 55o, marked by a thick horizontal line. We defined the acceptable error range as ±2o (dashed horizontal lines). (a) shows the result of the first session by

the sound-limbed subject ((c), amputee subject). (b) shows his result after training ((d), amputee subject).

 to 110o ) 281

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

control task, the subject was asked to achieve a series of eight different angles (from 0o

it there for only less than 2 s (period between points *A* and *B*).

showed on the screen of the GW.

asked to relax the muscles (point *B*).

**Figure 7.** Soften effect (*a*) obtained when a simulated pressure feedback PHS (*b*) was given to the simulator.

#### **3.2. Control experiments**

#### *3.2.1. Finger angle control*

We ran a control experiment to determine how accurately the subjects could control the finger angle of the simulator hand. The effects of using the simulator were also investigated by comparing the performance of the subjects before and after two trails. In this finger angle control task, the subject was asked to achieve a series of eight different angles (from 0o to 110o ) showed on the screen of the GW.

Figure 7(*b*) shows the value of the calculated *PHS* . When it reaches its maximal value, approx‐ imately 25 mV (roughly one third of its maximum), the difference between the fingers target

prosthetic hand (Okuno *et al.*, 1999), *PHS* gives self-control to the hand over the exerted force

**Figure 7.** Soften effect (*a*) obtained when a simulated pressure feedback PHS (*b*) was given to the simulator.

We ran a control experiment to determine how accurately the subjects could control the finger angle of the simulator hand. The effects of using the simulator were also investigated by

**3.2. Control experiments**

*3.2.1. Finger angle control*

. Therefore, as it happens with the real

angle with and without pressure feedback is nearly 10o

280 Electrodiagnosis in New Frontiers of Clinical Research

when grasping objects, producing a smoother grasping motion.

Figure 8 shows the typical results obtained, where the target angle to achieve was 55o (thick horizontal line). Figures 8(a) and 8(c) (left column) show the results of the first trial of two different subjects; (a) a sound-limbed subject and (c) the amputee subject. Both subjects needed more than 4 s to be able to keep the angle within the acceptable range, and were able to maintain it there for only less than 2 s (period between points *A* and *B*).

Figure 8(b) shows the results obtained by the sound-limbed subject after several trials for a period of about 40 min, and Figure 8(d) for the amputee subject after a similar period. In this case, both achieved the angle in just approximately 1 s (point *A*), and held it until they were asked to relax the muscles (point *B*).

**Figure 8.** Effect of training on position control (step response). The target angle was 55o, marked by a thick horizontal line. We defined the acceptable error range as ±2o (dashed horizontal lines). (a) shows the result of the first session by the sound-limbed subject ((c), amputee subject). (b) shows his result after training ((d), amputee subject).

To measure how accurately the subjects performed the task, we calculated the mean square error *ε* made while trying to keep a constant target angle *Θtarget* as

$$\varepsilon\_{\varepsilon} = \frac{1}{N} \sum\_{n=1}^{N} \sqrt{(\Theta\_{HS} \text{In} \text{J} - \Theta\_{target})^2} \tag{5}$$

This kind of powered myoelectric prostheses is not yet widely known. For example, in Japan only 350 units have been sold in the last 30 years (report of the Ministry of Health, Labour and Welfare of Japan). Our simulator could be accessible to physicians and related staff and be used to offer the opportunity to a wider group of amputees to try a myoelectrically controlled

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

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

283

The simulator can also be used for EMG signal processing and modeling. For example, when new features are added to the *Osaka Hand*, such as a new control program, the simulator can help in the design and testing phases, since it is easier and less expensive to make modifications

This simulator could be easily adapted to any myoelectric prosthesis, by performing just a few

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

G.A.G. thanks Professor Pedro García Teodoro (Granada University, Granada, Spain) for

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

and Kenzo Akazawa2

2 Department of Electrical and Electronic Engineering, Setsunan University, Osaka, Japan

[1] Abul-Haj, C., and Hogan, N. (1987): 'An emulator system for developing improved

elbow-prosthesis designs', *IEEE Trans. Biomed. Eng.*, 34, pp. 724-737

encouragement and scientific support during the first stages of this project.

prosthesis.

in the model than in the actual prosthesis.

Technology, Osaka University (Osaka, Japan).

, Ryuhei Okuno2

input on the original manuscript.

**Author details**

Gonzalo A. García1

**References**

1 Freelance, Bilbao, Spain

simple modifications on its software.

**Acknowledgements**

where *ΘHS n* is the hand simulator finger angle in the sample *n*, and *N* is the number of samples between the points *A* and *B*. We defined ±2o as the acceptable range of error (dashed horizontal lines in Figure 8).

The average of the error *ε* was 1.19o (s.d. 0.67) for the three non-amputee subjects and 1.78o (s.d. 0.54o ) for the amputee subject.
