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“Technique, style and performance in sport: biomechanical variations on a theme?”. By Carlton Cooke, Chris Low, Nassos Bissas, Giorgos Paradisis & Barney Wainwright (Carnegie Research Centre for Sport Performance). The presentation. Defining skill, technique, style and constraints (High Jump)

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    1. “Technique, style and performance in sport: biomechanical variations on a theme?” By Carlton Cooke, Chris Low, Nassos Bissas, Giorgos Paradisis & Barney Wainwright (Carnegie Research Centre for Sport Performance)

    2. The presentation • 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

    3. 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)

    4. Mechanics of the Fosbury flop • 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

    5. 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

    6. Analysis of technique • 3 main steps: observation - several aids developed evaluation - fault diagnosis intervention - poorly addressed

    7. Observation • 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

    8. Evaluation • 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)

    9. Hierarchical or deterministic models 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)

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

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

    12. ** **P<0.01 Group changes in max running velocity (MRV) Bissas PhD

    13. ** **P<0.01 Group changes in stride rate Bissas PhD

    14. Individual variation in response to training Bissas PhD

    15. Dynamical Systems Theory • 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.

    16. Dynamical Systems Theory • 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

    17. Environmental Perception Action Organismic Task (Davids et al., 2008) Dynamical Systems Theory(Newell 1986 model) Coherent framework for understanding how co-ordination patterns emerge during goal directed behaviour Functional co-ordination pattern selected under constraint

    18. Participant and performance • 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.

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

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

    21. Mean RMSD values between Kovacs Prep & Action and Longswings performed at different self-selected speeds Kovacs Prep = initial longswing Kovacs Action = longswing before Kovacs

    22. Kovacs and variations in longswings • 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)

    23. Conclusions on Kovacs & longswings • 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)

    24. What is next? • 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).

    25. The Uncontrolled Manifold (UCM) • 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).

    26. The Uncontrolled Manifold (UCM) • 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: • that indicates flexible combinations of elemental variables across trials leading to the same value of the performance variable or, • 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.

    27. Conclusion • 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.

    28. References Bartlett R. (2007) Introduction to Sports Biomechanics (2nd Ed.). Routledge Bartlett, R. Wheat, J. & Robins, M. (2007). Is movement variability important for sports biomechanists? Sports Biomechanics, 6, 224-243. Black, D. P. Riley, M. A. & McCord, C. K. (2007). Synergies in Intra- and Interpersonal Interlimb Rhythmic Coordination. Motor Control, 11, 348-373. Button, C. Macleod, M. Sanders, R. & Coleman, S. (2003). Examining movement variability in the basketball free-throw action at different skill levels. Research Quarterly for Exercise and Sport, 74, 257-269. Chow, J. Y. Davids, K. Button, C. & Rein, R. (2008).Dynamics of Movement Patterning in Learning Discrete Multiarticular Action. Motor Control, 12, 219-240. Dapena, J. (1980a) Mechanics of translation in the Fosbury-flop. Medicine and Science in Sports and Exercise, 12(1):37-44. Dapena, J. (1980b) Mechanics of rotation in the Fosbury-flop. Medicine and Science in Sports and Exercise, 12(1):45-53. Davids K., Button C., Bennett S. (2008) Dynamics of Skill Acquisition: A Constraints-Led Approach. Human Kinetics Davids, K. Glazier, P. Araujo, D. & Bartlett, R. (2003). Movement Systems as Dynamical Systems: The Functional Role of Variability and its Implications for Sports Medicine. Sports Medicine, 33, 245-260. Gates, D. H & Dingwell, J. B. (2008). The effects of neuromuscular fatigue on task performance during repetitive goal-directed movements. Experimental Brain Research, 187, 573-585.

    29. References Glazier P.S., Wheat J.S., Pease D.L., Bartlett R.M. (2007). The interface of biomechanics and motor control. In Davids K., Bennett S., Newell K (eds), Movement System Variability (pp. 49-69). Champaign, IL: Human Kinetics. Hay J.G. & Reid J.G. (1982). Anatomy, Mechanics and Human Motion. Prentice-Hall Inc. Kreigbaum E. & Barthels K. (1996) Biomechanics: A Qualitative Approach for Studying Human Movement, 4th Ed, Benjamin Cummings. Latash, M. L. Danion, F. Scholz, J. F. Zatsiorsky, V. M. & Schoner, G. (2003). Approaches to analysis of handwriting as a task of co-ordinating a redundant motor system. Human Movement Science , 22, 153-171. Latash, M. L. Scholz, J. F. & Schoner, G. (2007). Toward a New Thoery of Motor Synergies, Motor Control, 11, 276-308. Latash, M. L. (2008). Neurophysiological Basis of Movement. Human Kinetics. Lees, A. (2002). Technique analysis in sports: a critical review. Journal of Sports Sciences, 20, 813-828. Lees, A. & Barton, G. (2005) A Characterisation of Technique in the Soccer Kick Using a Kohonen Neural Network Analysis. Science and Football V: The Proceedings of the Fifth World Congress on Science and Football, 83-88. Low, C. & Cooke, C. (2008) Biomechanical Similarities of Longswings at Varying Speeds and the Kovacs Action. Proceedings of the 26th International Conference on Biomechanics in Sport, Seoul, Korea. Paradisis, G and Cooke, C (2001) Kinematic and postural characteristics of sprint running on sloping surfaces  Journal of Sport Sciences 19(2): 149-159.

    30. References Robins, M. Wheat, J. S. Irwin, G& Bartlett, R. (2006). The effect of shooting distance on movement variability in basketball, Journal of Human Movement Studies, 20, 218-238. Schollhorn, W. I. & Bauer, H. U. (1998). Identifying individual movement styles in high performance sports by means of self-organising Kohonen maps. Conference Proceeding Archive, 16 International Symposium on Biomechanics in Sport, 754-757. Scholz, J. P. & Schoner, G. (1999). The uncontrolled manifold concept: identifying control variables for a functional task. Experimental Brain Research, 126, 289-306. Scholz, J. P. Schoner, G. & Latash, M. L. (2000). Identifying the control structure of multijoint coordination during pistol shooting. Experimental Brain Research, 135, 382-404. Scholz, J. P. Reisman, D. & Schoner, G. (2001). Effects of varying task constraints on solutions to joint coordination in a sit-to-stand task. Experimental Brain Research, 141, 485-500. Schoner, G. & Scholz, J. P. (2007). Analyzing Variance in Multi-Degree of-Freedom Movements: Uncovering Structure Versus Extracting Correlations. Motor Control, 11, 259-275.