Table Of ContentAn Intelligent Prosthetic Hand using Hybrid
Actuation and Myoelectric Control
by
Beng Guey Lau
Submitted in accordancewith therequirements
forthedegreeof Doctorof Philosophy
TheUniversityof Leeds
School of Mechanical Engineering
October2009
Thecandidateconfirms that theworksubmittedis his/herownandthat appropriate
credit has beengivenwherereferencehas beenmadetotheworkofothers.
This copyhas beensuppliedontheunderstandingthat it is copyright material and
that no quotationfrom thethesis maybepublished
without properacknowledgement.
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Abstract
This thesis details the design and development of an intelligent prosthetic hand
based on hybrid DC and Shape Memory Alloy (SMA) actuation and controlled by
onlytwomyoelectricsensors.
A prosthesis as a tool makes no pretence of trying to replace the lost limb physio-
logically but it works as an aid to help provide some of the lost functions and is an
interchangeabledevicewornandusedas needed.
Much research has been carried out to develop artificial prosthetic hands with capa-
bilities similar to the human hand. The human hand is a verycomplex graspingtool,
that can handle objects of different size, weight and shape; however, they are far
from providingits manipulationcapabilities. This is formanydifferent reasons,such
as active bending is limited to two or three joints and user-unfriendliness. These
limitations are present in commercial prosthetic hands, together with others always
complained about by patients and amputees, such as inability to provide enough
grasping functionality and heavy weight. Several robotic and anthropomorphic
hands may have sufficient active degrees of freedom to allow dexterity comparable
to that of the human hand. Unfortunately, they cannot be used as prostheses due to
their physical characteristic that poses several serious limitations on human-hand
interaction.
Hence, the motivation for this research is to investigate the use of a hybrid actuation
mechanism in the design and development of an intelligent prosthetic hand. This
work highlights user-friendliness and involves a proper mechanical design with
moreactivedegrees offreedom andincorporatinganintelligent control system.
A system with a finger prototype is considered. Testing through simulation and
physical models reveals a number of limitations. A hybrid actuation system, to in-
crease the finger active degrees of freedom is therefore developed, with a mecha-
nism consisting of DC and SMA actuators. Besides, only two myoelectrodes chan-
nels (enhancing the user-friendliness of the device) are used for the system control
input signal.
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Two novel features are developed in the new prosthetic hand. Firstly, its hybrid ac-
tuation mechanism has the advantage of increasing the active degrees of freedom;
secondly, using onlytwo myoelectric sensors has potential for controlling more than
threepatterns offingers movements.
By using artificial neural network patterns classification technique, three and five
patterns of wrist joint movement corresponding to finger movement can be recog-
nisedas morethan85%correct andfurthermore,sevenas 70%correct.
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Acknowledgements
I’d like to thank a number of people each one of whom has helped me with his own
waythroughmyPhD. Icouldn’t havedoneit without you.
First of all I’d like to thank Mum, Dad, and the rest of my family for their love and
support throughout myfouryears ofstudies awayfrom them. This oneis foryou!
A special mention to my supervisors Dr. Abbas Dehghani and Dr. Robert. C.
Richardson for their support and concern and for giving me the opportunity to pre-
sent my work in a international conferences. It has been an honour studying and
workingbyyoursideall thoseyears. ThankyouAbbas andRobert.
A special thank you to Dr. David Gow, who is from Smart Centre, NHS Lothian, for
theencouragement,patienceand kindsupport. ThankyouDavid.
Thanks to the staff in the School of Mechanical Engineering that have helped me
through my time there. In particular Mr. David Readman and Mr. Steve Caddick
have been a great source of technical support and hoarded parts; thanks for all the
advice, help and teasing jokes! You have made my time in the labs fun and worth-
while!
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Contents
Abstract.......................................................................................................................i
Acknowledgements...................................................................................................iii
Contents....................................................................................................................iv
Listof Abbreviations.............................................................................................viii
Listof Figures............................................................................................................x
Listof Tables...........................................................................................................xv
CHAPTER1Introduction..............................................................................1
1.1 Background...............................................................................................1
1.2 Aim andobjectives....................................................................................3
1.2.1Objectives.........................................................................................3
1.3 Thesis outline............................................................................................5
CHAPTER2LiteratureReview.....................................................................7
2.1 Introduction...............................................................................................7
2.2 ActuationSystem Design..........................................................................9
2.2.1ReviewofActuators.........................................................................9
2.3 sEMGControl Input Signal....................................................................15
2.3.1SurfaceMyoelectrodes...................................................................17
2.3.2Signal ProcessingTechniques........................................................18
2.3.2.1 Dataacquisition...............................................................18
2.3.2.2 FeatureExtractionandSelection....................................19
2.3.2.2.1TimeDomain............................................................19
2.3.2.2.2FrequencyDomain....................................................21
2.3.2.2.3Time-ScaleDomain..................................................23
2.3.3PatternRecognition........................................................................29
2.3.3.1 FuzzyLogic.....................................................................31
2.3.3.2 Artificial Neural Network...............................................32
2.3.3.3 AdaptiveNeuro-FuzzyInferenceSystem........................34
2.4 SummaryandContributionofthis Project..............................................35
CHAPTER3Design of aProstheticFinger.................................................37
3.1 Introduction.............................................................................................37
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3.2 HandandFingerAnatomy......................................................................37
3.3 FingerDesign..........................................................................................39
3.3.1Dimensions.....................................................................................39
3.3.2Joints andDegrees ofFreedom......................................................41
3.3.3Material Selection..........................................................................41
3.4 ProstheticFingerKinematics..................................................................43
3.4.1ForwardKinematics.......................................................................45
3.4.2InverseKinematics.........................................................................50
3.4.3VerificationofClosedForm FormulaofInverseKinematics........54
3.5 Summary.................................................................................................55
CHAPTER4Hybrid Actuation Mechanism...............................................57
4.1 Introduction.............................................................................................57
4.2 DC Actuator............................................................................................57
4.2.1Force/TorqueoftheMCP Joint andProximal Phalanx.................60
4.3 SMAActuator.........................................................................................63
4.3.1LinearDisplacement ofSMAActuator.........................................63
4.3.2Force/TorqueofSMAActuator.....................................................70
4.3.3Experiment ofResult.....................................................................74
4.4 Summary.................................................................................................82
CHAPTER5Control SystemDesign of Actuation Mechanism................84
5.1 Introduction.............................................................................................84
5.2 DC Actuator............................................................................................84
5.2.1Modelling–System Identification.................................................85
5.2.1.1 AcquiringandPre-processingData.................................86
5.2.1.2 EstimationandValidationofModel...............................88
5.2.1.3 Model TransformationandAnalysis...............................97
5.2.2Control Design –Proportional Derivative...................................100
5.2.3Deployment..................................................................................104
5.3 ShapeMemoryAlloyActuator.............................................................107
5.3.1TimeResponse.............................................................................108
5.3.2Control Design.............................................................................110
5.4 Summary...............................................................................................111
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CHAPTER6SurfaceElectromyographyand its Signal Processing
Techniques....................................................................................................113
6.1 Introduction...........................................................................................113
6.2 Electromyography.................................................................................113
6.3 Myoelectrodes Sensor...........................................................................115
6.4 DataAcquisition....................................................................................116
6.4.1Equipment andProgrammingSetups...........................................116
6.4.2MethodologyforCollectingsEMGSignal..................................117
6.4.3Initial sEMGDataCollection.......................................................124
6.5 FeatureExtractionandSelection..........................................................125
6.6 Result ofOneTypical Signal................................................................130
6.7 Summary...............................................................................................132
CHAPTER7Pattern Recognition..............................................................135
7.1 Introduction...........................................................................................135
7.2 Fundamentals ofNeural Network.........................................................136
7.3 DataAssemblingandArrayManagement............................................140
7.3.1ThreePatterns ofMovement........................................................141
7.3.2FivePatterns ofMovement..........................................................142
7.3.3SevenPatterns ofMovement.......................................................145
7.3.4NinePatterns ofMovement.........................................................147
7.4 MethodologyforDesigningandTrainingNeural Network..................149
7.4.1Network’s Inputs Samples andTarget’s Array............................150
7.4.2NetworkCreation.........................................................................151
7.4.3NetworkSimulationandAccuracyofSimulatedNetwork..........152
7.5 Results andAnalysis ofPatternClassification......................................155
7.6 Summary...............................................................................................157
CHAPTER8Summary and Conclusions..................................................159
8.1 Assessment ofResearchObjectives......................................................159
8.2 Conclusions...........................................................................................161
8.3 FutureWorks.........................................................................................162
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REFERENCES......................................................................................................164
APPENDICES.......................................................................................................170
APPENDIXADC ActuatorSystem IdentificationModellingandPID
Control Design......................................................................................171
APPENDIXBDeployment ProgrammingofDC ActuatorControl
System...................................................................................................174
APPENDIXC LabViewEnvironment forsEMGDataAcquisitionin
TimeDomain........................................................................................182
APPENDIXDMatLabProgrammingforFeatures Extraction......................183
APPENDIXEMatLabProgrammingforNeural NetworkPattern
Recognition...........................................................................................187
APPENDIXFNeural NetworkPatternRecognitionforDifferent
Subjects.................................................................................................190
APPENDIXGPublishedWork.....................................................................191
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List of Abbreviations
ANFIS AdaptiveNeuro-FuzzyInferenceSystem
ANN Artificial Neural Network
AR AutoregressiveCoefficients
ARX AutoregressivewithExogenous Terms
ARMAX AutoregressiveMovingAveragewithExogenous Terms
CWT Continuous Wavelet Transform
DIP Distal Interphalangeal
DOF DegreeofFreedom
DP Distal Phalange
DWT DiscreteWavelet Transform
EAPs ElectroactivePolymers
EMG Electromyograph
FFTs Fast FourierTransforms
FL FuzzyLogic
IMES ImplantableMyoelectricSensor
logsig Log-sigmoid
MAV MeanAbsoluteValue
MCP Metacarpophalangeal
MP MiddlePhalange
MSE Meansquareerror
MVC Maximum VoluntaryContraction
Ni-Ti Nickel-Titanium
PID Proportional Integral Derivative
PIP Proximal Interphalangeal
PP Proximal Phalange
pureline lineartransferfunction
RMS Root MeanSquare
sEMG SurfaceElectromyography
SMAs ShapeMemoryAlloys
SOM Self-organizingmap
STFT Shoft TimeFourierTransform
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tansig tan-sigmoid
VAR Variance
WAMP Wilson Amplitude
WL Waveform Length
WT Wavelet Transform
Description:mechanism in the design and development of an intelligent prosthetic hand. This Two novel features are developed in the new prosthetic hand.
