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International Journal of Engineering Research in Africa
ISSN: 1663-4144, Vol. 18, pp 123-129
doi:10.4028/www.scientific.net/JERA.18.123
© 2015 Trans Tech Publications, Switzerland
Submitted: 2015-04-09
Revised: 2015-04-10
Accepted: 2015-08-18
Online: 2015-10-07
Experimental verification of force feedback for rehabilitation robot
MORE Marcel1,a*, LÍŠKA Ondrej1,b, KOVÁČ Juraj2,c
1
Technical University of Kosice, Faculty of Mechanical Engineering, Department of Automation,
Control and Human Machine Interaction, Letná 9, 04200 Košice, Slovak Republic
2
Technical University of Kosice, Faculty of Mechanical Engineering, Department of Robotics, B.
Němcovej 32, 04200 Košice, Slovak Republic
a
b
c
marcel.more@tuke.sk, ondrej.liska@tuke.sk, juraj.kovac@tuke.sk
Keywords: force feedback, force measurement, experiment, rehabilitation robot
Abstract. Unlike conventional robots, the equipment provided with pneumatic artificial muscles
cannot integrate standard systems for force measurement. Applied measurement system involves
specific attributes and requirements for pneumatic muscles. Force feedback of rehabilitation device
equipped with pneumatic muscles was experimentally verified under the laboratory condition.
Introduction
Rehabilitation robot driven by pneumatic artificial muscles (pneumatic artificial muscles PAM),
developed at the Faculty of Engineering Technical University of Kosice is intended for
rehabilitation of the upper limb joints (Fig. 1). It is pluri-articular i.e. it will practice several joints
simultaneously. Each of the arms is driven by two pneumatic muscles in antagonistic involvement,
controlled by solenoid (electro-magnetic) valves [1-4]. Device shall include a multilevel controlling
system.
Force feedback is an essential part of an automated device that is intended for active
rehabilitation. In the device which is driven by the pneumatic artificial muscles, the force/strength
measuring system cannot be used as it is in the conventional robots [5-7]. Therefore it is necessary
to design a measurement system considering the specific characteristics and requirements of such
equipment [8,9].
Analysis shows that the loading strength can be measured: at the point of contact of the robot
with the man, on the robot arm or in drive itself [1]. Three measurement methods were selected for
experimental verification. The first one is the measurement in the device handle via touch sensors
FSR. Other methods are based on the knowledge that the force applied to the robot arm creates a
corresponding reaction in the drive. Load for actuator with pneumatic muscle can be determined
from the change in filling pressure in each muscle. Load is also reflected in the mechanical parts of
the drive and transmission, where it can be measured using the strain-gauge load cell (sensors).
Measuring the force applied on the handle of rehabilitation device
Card Humusoft MF624 is used when measuring the force applied on the handle of rehabilitation
device and its transfer to the signal. Card is used to obtain data for Matlab-Simulink in which the
controller device is designated.
FSR Sensors
FSR (Force Sensitive Resistor) consists of thin layers of polymer. When the effective surface is
loaded by the force, electrical resistance of polymers decreases [10-12]. Their sensitivity is
optimized for use of human touch [13-15]. Therefore the sensors are placed in the handle unit.
These are located on a flexible backing and covered with a layer of rubber. Electrical connection is
based on sensor function. They work as variable resistors. Sensors are connected in series with
resistors having a constant resistance, and form a voltage divider. Resistor values are calculated
All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans
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International Journal of Engineering Research in Africa Vol. 18
with respect to the measuring range of the sensors. Output divider with the largest margin ensures
measurement with the highest resolution. Measuring chain for the FSR sensor represents Figure 2.
Fig. 1 Prototype of rehabilitation device driven by PAM
Fig. 2 Measurement chain for FSR sensors
Pressure sensors
Muscle loaded up is changing its length. By changing the length also the volume of muscle varies
and in closed system it causes pressure changing. Pressure in muscles determines the force which
Journal of Engineering Research in Africa Vol. 18
125
the arm of rehabilitation robot is loaded up. Values of pressure in the muscles determine the force
which arm rehabilitation device is loaded up. It allows applying sensors for measuring the pressure
in the pneumatic muscles in the range of 0-6 bar which have compatible output. Sensors
SSCDANT005PGAA5 were used in the experiment. While pressure regulating in muscle,
fluctuation of pressure occurs therefore pressure sensors were placed as close as possible to the
muscle [16-19]. Pressure fluctuation in this case is the smallest. Measuring chain for pneumatic
pressure sensor is in Figure 3.
Fig. 3 Measurement chain for pneumatic pressure sensor
Strain-gauge load sensors. Drive load is determined by measuring the voltage on transmission.
Experimental device uses for power transmission the wires integrated in bowdens. Sensors were
placed between the wire and the pneumatic muscle. In this case there is a load on the axis of the
wire. To measure the tensile and compressive stresses were applied strain-gauge sensors EMS30.
Sensors do not directly produce signal therefore the measuring system contains the electronic units
EMS168 which provides the required power. Signal is amplified and filtered to yield normalized
voltage and current output. Measuring chain for load cells is described in Figure 4.
Fig. 4 Measurement chain for strain-gauge sensors
Experiment
Measuring chains were applied on evolved rehabilitation device and their response was tested
against the load on arm by strength. Measurements were repeated under the same conditions in all
experiments.
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International Journal of Engineering Research in Africa Vol. 18
Aim of the study was to investigate the dispersion of values obtained by different measurement
methods for repeated loading constant force [20-22]. While comparing the results factors that affect
the various different forms of measurement were eliminated.
The effect of gravity is eliminated by placing the arm device in the way that the centre of the
operating range is perpendicular to the ground. Because the device has several degrees of freedom,
these while loading would transfer the strength out of the measuring chain [23-25]. Therefore all the
joints in which the measurement does not occur were fixed. Subsequently, the pneumatic muscles
propelling joint inflate the working pressure which lead to close of pneumatic system [26]. By a
simple device that allows producing constant load, the arm was burden alternately on both sides.
The reason for the symmetrical loading was that use of pneumatic muscle leads to creeping. This
causes a change of the average value according to the number of repeated measurements.
For data measuring the program created in Matlab-Simulink was used. Signals from sensors were
processed by measuring card MF624. Signal measured by this card was used directly in Simulink.
All input signals are filtered by a low pass filter to remove the fluctuations of values. Whereas the
measurement was conducted as static, the filter did not affect the process of the measured values.
Prepared program stores the value in a file format that handles Microsoft Excel. Record of measured
values was processed in Matlab-Simulink.
Results of experiments
The experiments were repeated in four batches or series respectively. Each contains 30
measurements. In each measurement was recorded load value. This value is in all measurement
modes determined as the difference between the values of the two sensors (air pressure difference in
muscle, the voltage difference in the cable, etc.). These values cannot be directly compared, since
each type of sensor measures with different strength loading or zero offset. Therefore all values are
first converted to the same range (0-100) by the formula (1).
Fig. 5 Graph of adjusted values measured within one of series
Journal of Engineering Research in Africa Vol. 18
127
X max was used as the highest load value in the series of measurements.
Xadapted = (
Xmeasured
) × 100
X max
(1)
Graph of the adjusted values of one set of measurements is shown in Fig. 5. Dispersion of the
measured FSR sensors is much greater than for the other methods of measurement. As the number
of measurements or time respectively increases, the average value of FSR sensors is primarily
deviating.
Correlation of the strain-gauge values and values of the pressure sensors shows that the origin of the
dispersion is not in the sensor itself, which measure the load on the drive, but may be formed e.g. in
the transmission or at the load device.
From each series of measurements was calculated experimental variance of the formula (2)
where n is the number of measurements in the series, X is the measured value and is the average of
the values in the series. Calculated results are in Table 1.
1 n
s =
∑ ( X −)
n − 1 i =1
2
2
(2)
Results of all series measurements show that the most promising method is the measurement of
strain-gauges. FSR sensors exhibit high variance. It is not advisable to use them as a single
measurement method [27-29]. They can be complementary to another method of measurement (e.g.
check the correct grip). Load measuring with pressure sensors (Tab. 1) has a high instability. With
dynamic load these deviations measurements even multiply, so the method is not suitable for
measuring the load.
Measurement of strain-gauge sensors provides the smallest scattering measurements, but even
the smallest differences between series of measurements and the positive and negative direction of
loading [30,31]. This method is best placed to form force feedback rehabilitation equipment driven
by pneumatic artificial muscles.
Table 1 Variance of load measurement by different methods
Positive deflection
Pressure
Strain-gauge
sensor
FSR
sensors
Negative deflection
Pressure
Strain-gauge
sensor
FSR
sensors
Series 1
19.605
131.307
19.403
27.118
185.416
29.164
Series 2
127.495
101.365
33.551
37.424
184.186
15.311
Series 3
68.785
119.652
30.737
48.126
207.223
27.092
Series 4
100.876
104.683
39.976
33.700
262.262
24.966
Average
79.190
114.252
30.917
36.592
209.772
24.133
Conclusion
Force feedback for rehabilitation device driven by pneumatic artificial muscles due to its
specific characteristics and requirements must be different from the systems used in other robots.
Analysis verified three assessment methods, which were designed for measuring chains. In specific
terms, which should eliminate adverse impacts, there were performed and evaluated thirty-four
series of repeated load measurements with constant force.
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International Journal of Engineering Research in Africa Vol. 18
Acknowledgement
Contribution was prepared with the support of EU Structural Funds, Operational Programme
Research and Development, Measure 2.2 Transfer of knowledge and technology from research and
development into practice, the project "Research and development of intelligent unconventional
actuators based on artificial muscles" ITMS 26220220103 and also with the support of project
VEGA 1/0911/14 "Application of wireless technologies in new products and services for the
protection of human health."
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