Anatomical and Functional Based Upper Limb Models: Methods for Kinematic Analysis of Cricket

237 Pages·2009·2.96 MB·English

by  Aaron Chin

Anatomical and Functional Based
Upper Limb Models: Methods for
Kinematic Analysis of Cricket Spin
Bowling

Aaron Chin

Bachelor of Science (Honours)

This thesis is presented for the degree of Doctor of
Philosophy of Science of The University of Western Australia

School of Sport Science, Exercise & Health

2009
"The one quality all successful people have is persistence. They're
willing to spend more time accomplishing a task and to persevere in the
face of many difficult odds."

--- Dr Joyce
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ABSTRACT

In cricket, the bowler propels a ball using a straight arm (permitted minimal extension)
in an overhead fashion to a batsman situated approximately 20m away, who attempts to
strike the ball in order to score runs for their team. Cricket bowling can be generalised
by two types of bowlers; fast bowlers, who primarily use high ball speed, and spin
bowlers that attempt to impart spin on the ball causing it to bounce in different
directions. There has been numerous studies investigating the kinematics of fast
bowling in cricket, but there is a paucity of objective literature on the spin bowling
action due to the complex rotations of the upper limb necessary to develop ball velocity
and rotation. One primary reason is that three dimensional (3D) analysis of upper limb
movement is difficult due to the high degrees of freedom and ranges of motion of the
associated joints. Furthermore, existing methods do not allow measurement of the
kinematics of this highly dynamic task to be performed in an ecologically sound
environment.

The complexity is further compounded as the upper limb does not perform regular
cyclical movements like the lower limb does with gait. Therefore, this makes it difficult
to determine what „normal‟ upper limb patterns of movement are during activities of
daily living. Methods and procedures can be performed to reduce the variability
associated with 3D analysis of upper limb movements and in doing so, improve the
quality of upper limb assessment. Previous methods have used anatomical landmarks to
identify segments and the position and orientation of these segments with respect to
each other whilst other approaches have utilised functional movements of the joints to
determine axes of rotation. This second approach may improve analysis by reducing the
error and variability associated with more traditional methods of placing markers on
anatomical landmarks to determine joint kinematics.

Therefore, the primary aim of this research was to develop and validate a functionally
based 2 degree-of-freedom upper limb model using a mean finite helical axis method
(HAM) to measure rotations of the forearm using a marker based approach. A
mechanical arm was constructed to replicate the upper limb whereby the location of the
joint axes and ranges of motion were known. The arm was then used to validate the
accuracy of the model compared to an anatomically based model (ANAT) that followed
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the proposed International Society of Biomechanics (ISB) standardisation. Additionally,
in vivo analysis was performed on 10 male participants (23.5±2.7years, 180.5±7.9cm) to
determine the location of the axes of rotation relative to anatomical landmarks.

Both modelling approaches were able to accurately record the ranges of motion to
within 2° of the known values. Although accurate, cross-talk was evident within the
ANAT model despite only pure flexion-extension (F-E) rotations being performed with
the mechanical arm. In contrast, the functionally based HAM model did not record
rotations about the other axes and was thus not influenced by adduction-abduction
cross-talk. Results from the in vivo aspect of the study indicated that the functional
elbow F-E axis lies at an angle of 6.6º±4.1º to an anatomical line defined between the
two lateral epicondyles of the humerus. The pronation-supination (P-S) axis intersected
this anatomical line at an angle of 88.1º±2.6º.

As mentioned previously, inaccurate identification of joint axes results in high
variability of kinematic data. As such, the second aim of this research was to investigate
the intra- and inter-tester repeatability of three models; the two used in the first study
(HAM and ANAT), and an anatomically based model provided within the Vicon
Bodybuilder software (Plug-in Gait). Five examiners collected upper limb movement
data of 10 male participants over three sessions. Upper limb data waveforms were then
analysed for similarity using Coefficients of Multiple Determination (CMDs). Data
from each session were then analysed using a Friedman‟s ANOVA.

All three models in the study produced highly repeatable elbow F-E kinematic
waveforms for both intra- and inter-tester conditions. However, although the Plug-in
Gait model was highly repeatable, different kinematics were observed in comparison to
the other two models. Furthermore, repeatability of HAM and ANAT kinematic data
was more repeatable in the intra-tester condition for P-S compared to inter-tester. The
HAM model was more repeatable than the ANAT model for both conditions, most
likely due to the model not relying on accurate location of anatomical landmarks. From
this study it was concluded that repeatability of kinematic data can be increased with a
functionally based model and may be of particular importance in settings whereby data
comparisons need to be performed over several different examinations.

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With a functionally based model developed, validated, and its repeatability assessed, the
third aim of this research aimed to investigate kinematic variation of cricket spin
bowlers of varying playing levels to create ball velocity and spin. A 12 camera Vicon
system recorded the off-break bowling actions of 6 elite and 13 high-performance
players. Additionally, the „doosra‟ bowling action of 4 of these elite and 2 high-
performance players was assessed. Data between the playing levels and the two delivery
types were analysed.

From the anatomical data collected, the elite players displayed more forearm abduction
(carry angle) and fixed elbow flexion. Higher ball velocity and a greater amount of ball
rotation were recorded for the elite group when bowling the off-break. A greater amount
of pelvic rotation by the elite group recorded high effect size. The elite group also
displayed a greater range of elbow extension between the period upper arm horizontal
and ball release which may be highly related to the higher ball spin and velocity. In
comparison to the off-break delivery, the „doosra‟ was characterized by larger ranges of
shoulder horizontal rotation, elbow and wrist extension. Furthermore, the lower ball
release height and longer stride length measured when bowling the „doosra‟ were
significantly different, with high effect sizes for the measured variables pelvis rotation
and elbow extension. This study provides an initial quantitative analysis of the finger-
spin bowling action having established several characteristics that differentiate between
off-break deliveries of elite and first class players. Likewise, kinematic variations
between the off-break and „doosra‟ deliveries have been measured.

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TABLE OF CONTENTS

Page
Abstract i
List of Figures ix
List of Tables xiii
Acknowledgements xv
Publications Arising From This Thesis xvi
Statement of Candidate Contribution xvii

Chapter 1: General Introduction
1.1 Background and Research Rationale 2
1.2 Statement of the Problem 5
1.3 Aims of the Research and Hypothesis 6
1.3.1 Study 1: A marker based mean finite helical axis model to
determine the location of elbow axes and kinematics in vivo 6
1.3.2 Study 2: Repeatability of upper limb kinematic data using a
two degree of freedom elbow model 7
1.3.3 Study 3: The off-break and Doosra: Kinematic variations of
elite and sub-elite bowlers in creating ball spin in cricket 7
bowling
1.4 Thesis Outline 8
1.5 Definition of Terms and Abbreviations 9
1.6 Delimitations 10
1.7 Limitations 10

Chapter 2: Literature Review
2.1 Introduction 12
2.2 Anatomy of the Elbow 12
2.3 A Brief History of Motion Analysis 14
2.4 The Development of Upper Limb Models 15
2.4.1 General Overview of Biomechanical Modelling Procedures 16
2.4.2 Traditional Anatomically Based Models 18
Marker Placement 18
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Determination of Shoulder JC 19
Determination of Elbow JC and Axes 20
Determination of Wrist JC and Axes 21
2.4.3 Numerical and Functionally Based Models 21
2.5 Repeatability of Kinematic Data 23
2.6 Cricket Bowling Biomechanics 27
2.6.1 Applications to Cricket Coaching 27
2.6.2 Spin Bowling Analysis 28
2.7 Summary of Literature Review 34

Chapter 3: Methods and Procedures
3.0 Introduction 37
3.1 Study 1 - A marker based mean finite helical axis model to determine
the location of elbow axes and kinematics in vivo 37
3.1.1 Construction of Mechanical Limb 37
3.1.2 Model Development 41
3.1.2.1 Marker Set 42
Upper-Arm Technical CS 43
Forearm Technical CS 43
3.1.2.2 Determination of Shoulder Joint Centre (SJC) 44
3.1.2.3 Determination of Elbow Joint Centre (EJC) 45
Pointer Method 45
Anatomical (ANAT) Model 47
Helical Axis Method (HAM) Model 48
3.1.2.4 Determination of Wrist Joint Centre (WJC) 51
3.1.2.5 Segment and Joint Coordinate Definitions 51
Upper Limb Anatomical CSs – Anatomical Method 52
Upper Limb Anatomical CSs – Functional Method 52
Forearm Anatomical CSs 53
Hand Anatomical CS 53
Joint CS of the Elbow 57
3.1.3 Laboratory Setup 57
3.1.4 Data Collection Protocol 58
3.1.4.1 Mechanical Arm 58
3.1.4.2 Bowling Subject Protocol 59
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3.1.5 Data Analysis 60

3.2 Study 2 - Repeatability of upper limb kinematic data using a two
degree of freedom elbow model 60
3.2.1 Participants 60
3.2.2 Subject Preparation and Marker Placement 61
3.2.3 Camera Setup 61
3.2.4 Session Protocol 62
3.2.5 Analysis Protocol 62
3.2.6 Data Processing 65
3.2.7 Statistical Analysis 65
3.3 Study 3 - The off-break and Doosra: Kinematic variations of elite
and sub-elite bowlers in creating ball spin in cricket bowling 66
3.3.1 Participants 66
3.3.2 Marker Placement and Determination of Anatomical CSs 66
3.3.2.1 Upper Body Marker Placement and Segment
Definitions 67
Head 67
Thorax 68
3.3.2.2 Lower Body Marker Placement and Segment
Definitions 69
Hip and Knee JC Estimation 70
Femur/Thigh Segment 70
Tibia/Shank Segment 71
Foot Segment 71
3.3.2.3 Ball Marker Placement 71
3.3.2.4 Joint Angle Definitions 72
3.3.3 Camera and Laboratory Setup 73
3.3.4 Data Collection Protocol 76
3.3.5 Statistical Analysis 77

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Chapter 4: A marker based mean finite helical axis model to determine
the location of elbow axes and kinematics in vivo
4.1 Abstract 79
4.2 Introduction 80
4.3 Methods 82
4.4 Results 84
4.5 Discussion 90
4.6 Conclusion 92

Chapter 5: Repeatability of Upper Limb Kinematic Data Using a Two
Degree of Freedom Elbow Model
5.1 Abstract 94
5.2 Introduction 95
5.3 Methods 96
5.4 Results 100
5.5 Discussion 103
5.6 Conclusion 105

Chapter 6: The Off-break and Doosra: Kinematic Variations of Elite and
Sub-elite Bowlers in Creating Ball Spin in Cricket Bowling
6.1 Abstract 108
6.2 Introduction 109
6.3 Methods 109
6.3.1 Participants 109
6.3.2 Camera and Laboratory Setup 110
6.3.3 Data Collection and Procedures 110
6.4 Results 112
6.4.1 The Off-Break Delivery 113
6.4.2 The Doosra Delivery 118
6.5 Implications for Performance 121
6.6 Conclusions 124

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Chapter 7: Summary, Conclusions and Future Research
7.1 Summary 126
7.2 Conclusions and Recommendations for Future Research 129

List of References 131

Appendices
Appendix A Study 1: Subject Information Sheet and Consent Form 137
Appendix B Study 2: Subject Information Sheet and Consent Form 141
Appendix C Study 3: Subject Information Sheet and Consent Form 145
Appendix D UWA Full Body Static Bodybuilder Model 149
Appendix E UWA Full Body Dynamic Bodybuilder Model 167
Appendix F Cricket Ball Model 200
Appendix G Matlab Syntax to Calculate Elbow Helical Axes 207

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