By
Carlton Cooke, Chris Low, Nassos Bissas, Giorgos
Paradisis & Barney Wainwright
(Carnegie Research Centre for Sport Performance)








Defining skill, technique, style and constraints (High
Jump)
Analysing technique – 3 main steps
Biomechanical Models – understanding variations in technique and style in performance (Kayak paddling)
Variations in response to training (Sprint running)
Dynamical systems theory (Gymnastics)
The Uncontrolled Manifold (Football)
Conclusion

Definitions:
Biomechanical classifications of movement
• General Movement Patterns (e.g. Jumping)
• Skill (e.g. High Jump)
• Technique (e.g. Fosbury Flop)
• Style (Individual variation in the performance of Technique)
• Primary Mechanical Purpose (height of clearance, Objective/Outcome/Performance)
(Kreighbaum & Barthels, 1996)


Approach velocity is a predictor of height jumped

Hip height at take off is a predictor of height jumped

Why do some international high jumpers
“buckle” ?
(i.e. not even leave the ground)

Not all Fosbury flops are the same (variation)
Dapena (1980a and b) Medicine and Science in Sports and Exercise

Factors effecting “Style” in Fosbury flop

Factors effecting “Style” i.e. constraints
• Leg strength and power
• Flexibility
• Height
• Weight
• Body composition
• Individual constraints are variable between jumpers
• What about variations within a jumper between attempts?
Dapena (1980a and b) Medicine and Science in Sports and Exercise


3 main steps: observation - several aids developed evaluation - fault diagnosis intervention - poorly addressed




Phase Analysis - descriptive process to divide movements into constituent parts
Temporal Analysis - builds on phase analysis by specifying the timing of a movement
Critical Features - components of movement that are essential to the performance of a skill

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


Coaching Manuals - descriptive templates based on expert performance
Diagnosis of faults determined by deviations from the template
Aware of variations in performance level and individual differences
Criticisms of this approach based on premise that success and high technical skill have a reciprocal relationship (Hay & Reid, 1982;
Bartlett, 2007)

The model must be based upon fundamental mechanics that govern the movement, and each factor must be completely determined by those factors that appear in the level directly below it.
(Glazier et al., 2007; Hay & Reid, 1982)

Novel Sprint Running Training
(uphill-downhill ramp 3 degree slope)
(

)
DCM
(

)
Bissas and Paradisis (PhDs)
(

)
(

)


Running Speed

DCM TO
Physique
 knee angle (

)
 hip angle (

)
 shank angle (

)
 trunk angle (

)
 thigh angle (

)



Step Length
DCM TD
Posture

Step Rate

Flight Distance



Contact Time
Step Time

Flight Time
Eccentric

Concentric
Acceleration (g)
Height TO
Air Resistance
Speed TO
Velocity TD Velocity change
Force Exerted Time Forces Act
Paradisis and Cooke (2001) Journal of Sports Sciences

Group changes in max running velocity (MRV)
Bissas PhD
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
Training
**
Control
**P<0.01

0.1
0
-0.1
0.3
0.2
-0.2
Training
**
Control
**P<0.01
Bissas PhD

Individual variation in response to training
Bissas PhD
25.0%
Improvement
20.0%
15.0%
10.0%
5.0%
0.0%
-5.0%
-10.0%
MRV
SR
SL
CT
FT
Decline
N=10
4.0%
3.6%
0.5%
4.7%
2.3%
P1
2.4%
6.3%
-3.8%
6.7%
5.6%
P2
-1.4%
0.0%
-1.4%
6.7%
-5.9%
P3
6.4%
3.2%
3.2%
5.9%
0.0%
P4
2.4%
2.7%
-0.5%
5.6%
0.0%
P5
3.4%
3.5%
0.0%
6.3%
0.0%
Participants
P6
5.5%
3.0%
2.3%
6.3%
0.0%
P7
9.1%
6.6%
2.2%
0.0%
11.1%
P8
11.1%
10.2%
0.7%
0.0%
18.8%
P9
1.9%
0.0%
1.9%
0.0%
0.0%
P10
2.5%
0.0%
2.5%
5.9%
-7.1%

 Motor control theory that looks at how multiple degrees of freedom are controlled (Utley & Astill,
2008)
 The athlete is considered as a complex, biological system (Davids et al., 2008)
 Consider the system as a whole, where the parts of the system interact and affect each other.

 Functional role of variability in analysis of movement
 DST contrasts with information processing view that variability is noise in the sensorimotor system that needs to be removed
 In DST concept of representative trial does not exist

Coherent framework for understanding how co-ordination patterns emerge during goal directed behaviour
Environmental
Organismic Task
Perception
Action
Functional co-ordination pattern selected under constraint
(Davids et al., 2008)

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
A former member of the men’s national gymnastics squad performed one trial of 12 continuous backward longswings on the Men’s
Horizontal Bar at self-selected speeds in the following order: 3 normal, 3 fast, 3 slow, 3 fast
He then completed a second trial performing a
Kovacs. All trials were performed on a standard competition high bar.


Qualisys Capture System
 Capture freq:150Hz
 Ave. Residual of cameras <
1mm

S.D. Wand length 2mm

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Motion data into
Visual3D
Butterworth filter with cut-off at 10Hz
Calculated planar angles at shoulder and hip wrist shoulder knee hip

Mean RMSD values between Kovacs Prep &
Action and Longswings performed at different self-selected speeds
θ
S
(°)
ω
S
(°s
-1
)
θ
H
(°)
ω
H
(°s
-1
)
Kovacs Prep
Kovacs Action
Kovacs Prep
Kovacs Action
Kovacs Prep
Kovacs Action
Kovacs Prep
Kovacs Action
Normal
5
6
46
61
7
22
70
183
Kovacs Prep = initial longswing
Fast 1
5
6
47
56
7
19
54
156
Kovacs Action = longswing before Kovacs
Slow
5
7
56
62
7
23
73
183
Fast 2
6
5
47
51
5
18
41
151




The lower RMSD values for the fast longswings indicates that varying the speed of the longswing can lead to greater similarities between the longswing action and the Kovacs skill.
Functional variability of the longswing action may therefore be useful in the acquisition of the Kovacs, suggesting that longswing progressions should encourage the development of variable longswing movements.
Interestingly, there were greater similarities in the hip joint motion observed in the fast longswings performed after a series of slower longswings, suggesting that sequence of speed variation may be important.
Low and Cooke (2008)


Sequential variation in the speed of longswings induced movements that have a greater similarity to those movements associated with a high level skill.

Functional variability in the longswing action may therefore be beneficial to gymnasts in terms of acquisition of high level skills, such as the Kovacs.
Low and Cooke (2008)




Chris will keep working on gymnastics
New PhD student looking at intra subject variability in football kicking
Both will be looking at the possibility of partitioning variability into functional and dysfunctional variation using a quantitative technique known as the “uncontrolled manifold” (UCM) (Latash et al, 2003).

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The UCM establishes if trial-to-trial variability of elemental variables shows a stability in performance variables (Latash et al, 2007).
The elemental variables describe degrees of freedom in the motor system for the task.
The performance variable(s) describe what is essential in fulfilling the task variable (e.g. foot position and velocity when kicking the ball).
The task variable depends on the outcome of a specific performance variable (e.g. the task variable of kicking accuracy is dependent on the performance variable of foot position relative to the ball at the time of the kick).


The UCM links the variance of elemental variables and variance of a performance variable, using the Jacobian matrix.

The Jacobian matrix partitions the variance of the elemental variables into two:
1.
that indicates flexible combinations of elemental variables across trials leading to the same value of the performance variable or,
2.
changes in the performance variable.

If 1 is greater than 2 the performance variable is stabilised by compensation among the elemental variables and a SYNERGY is said to exist . The higher 1 is, the greater the amount of compensated variability, which suggests a stronger synergy and more stability.

Therefore, the UCM goes beyond analysing the variability within a technique by also indicating whether the variability is useful or not.



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Variability can be positive and negative in sports-specific tasks
Variation can assist in providing flexible movement solutions for successful performance
Constraints can limit performance
Understanding the different dimensions of inter and intra variability in technique, style and how they do or don’t explain performance in sport is key to not only biomechanists, but also performers, coaches, and teachers.

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