UWE Bristol Engineering showcase 2015

Sean Christoph Gordon
BEng Mechanical Engineering
Project Supervisor
Dr Appolinaire C. Etoundi
Automated Exoskeleton Arm System
Introduction
Stroke is the most common cause of severe disabilities in the
developed world. Over 1/3 of stroke victims sustain long-term
moderate to severe disabilities including motor limitation in the
extremities with hand function often impaired following stroke and
only 14% of stroke survivors recover full sensory motor function in the
arm.
Design Aspects Chosen Option Reason
Body Off-the-shelf design (anglepoise lamp) Simple, readily available, less time
spent on designing the body and more
on the core system.
Spring System None Provided in the option chosen for the
Body criterion.
Actuation System Servomotor (miniscule version) Not too bulky, very cheap, easy to
interface.
Detection System Strain Gauges Easy to use, testing rig available in
laboratory, cheap.
Microprocessor Arduino (Uno) Simple, basic, cheap.
Evaluation
The potentiometer served as the stand-in for the strain gauge due to resource
limitations. The LCD that was linked to the potentiometer would, in actual
fact, be linked to the strain gauge but would function in the same way. The
motor used was not as strong or large as it should have been (again, limited
due to resource) to accommodate for a bigger weight and size however, the
connections would remain the same regardless. An increase in power output
may be necessary to power such a motor which has been proven that it can be
done with the Arduino Uno
Through the calculations and the feasibility of the
system, the data transfer that occurred can be
interpreted with a good degree of reliability. For
example, if a load of 150g was applied to the arm of
the patient, the strain gauge would read 56µε which
would equal a value of around 4.3V. This value would
be sent to Arduino (which would be displayed on the
LCD screen) and the motor would move by around
60°. The arm would be raised by the same amount
and thus, the weight would have been lifted up. The
same applies for situations where the arm flexes to
equate a weightage of 150g.
Theoretical Data
25
20
15
10
5
0
Comparison between Different Theoretical Data Entries for 50kg Body Weight
0 15 30 45 60 90
Angle of Arm from Vertical (degrees)
Weight (g) Distance Moved (degrees) Voltage (V) 10-bit code
105 8 3 590
112 16 3.2 629
120 24 3.4 668
125 32 3.6 707
132 40 3.8 746
140 48 4 785
145 56 4.2 824
153 64 4.4 863
162 72 4.6 902
169 80 4.8 941
175 88 5 980
Torque (Nm)
Energy (J)
Power (W)
The theoretical calculations made further
enhances the data that would be gathered for
such a situation. If the patient weighs 50kg and
has the average arm length of 0.4m, the torque
produced by his/her arm to move by 60° would
be 9.05Nm. Subsequently, the energy produced
would equate to 8.98J and the power value
would be 3.16W. Compiling all the information
would allow the physiotherapist to prescribe
more suitable exercises and monitor recovery
rate.
Project summary
Using exoskeletons for therapy for stroke patients is
not a new concept. However, most exoskeletons
make use of a controller and are usually specifically
controlled by the doctors rather than the patients.
Having an automated system for these exoskeletons
would allow the patients more independency from
the doctors to help promote a healthier form of
recovery.
Project Objectives
The system would connect the biceps of the arm to a
motor that would drive the arm. The project is aimed
towards stroke patients who possess at least partial
motor control in their arm. Attaching a strain gauge
to the arm would mean that for any change in strain,
the strain gauge would read that value and translate
it into a motor movement by means of a
microprocessor. This would allow the patient to drive
their arm by means of just wanting to move their
arm.
Project Conclusion
The automated system was built, tested and proved
that it can work. Though actual skin-mounted strain
gauges were not used, the feasibility of the system
was still proved nevertheless. The theoretical
calculations made would allow for the system to
successfully predict the force, torque, energy and
power of the arm with variability in the weight and
position of the arm, in any combination whatsoever.