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On analysing and interpreting variability in motor output

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Paul Glazier
Paul Glazier
Keith Davids at Sheffield Hallam University
Keith Davids
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Abstract

A recent article in the Journal of Science and Medicine in Sport by Chapman et al.1 reported data from an empirical investigation comparing lower extremity joint motions, joint coordination and muscle recruitment in expert and novice cyclists. 3D kinematic and intramuscular electromyographic (EMG) analyses revealed no differences between expert and novice cyclists for normalised joint angles and velocities of the pelvis, hip, knee and ankle. However, significant differences in the strength of sagittal plane kinematics for hip–ankle and knee–ankle joint couplings were reported, with expert cyclists displaying tighter coupling relationships than novice cyclists. Furthermore, significant differences between expert and novice cyclists for all muscle recruitment parameters, except timing of peak EMG amplitude, were also reported.
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Journal of Science and Medicine in Sport 12 (2009) e2–e3
Letter to the Editor
On analysing and interpreting variability in motor output
A recent article in the Journal of Science and Medicine
in Sport by Chapman et al.1reported data from an empirical
investigation comparing lower extremity joint motions, joint
coordination and muscle recruitment in expert and novice
cyclists. 3D kinematic and intramuscular electromyographic
(EMG) analyses revealed no differences between expert and
novice cyclists for normalised joint angles and velocities of
the pelvis, hip, knee and ankle. However, significant dif-
ferences in the strength of sagittal plane kinematics for
hip–ankle and knee–ankle joint couplings were reported, with
expert cyclists displaying tighter coupling relationships than
novice cyclists. Furthermore, significant differences between
expert and novice cyclists for all muscle recruitment param-
eters, except timing of peak EMG amplitude, were also
reported.
Perhaps the most theoretically interesting finding to
emerge from this study was that novice cyclists exhibited
significantly greater variability in hip–ankle and knee–ankle
joint couplings than expert cyclists. From an information pro-
cessing theoretical perspective, it could be argued that these
results, taken at face value, support the proposition that motor
learning is characterised by progression towards invariance
in motor output2and that movement variability might be a
negative by-product of noise in the central nervous system
that should be minimised or eliminated.3–5 However, from
a dynamical systems theoretical perspective, observed vari-
ability in motor output in both novice and expert cyclists
may not necessarily be a reflection of system noise. As
motor learning from a dynamical systems theoretical perspec-
tive is considered to be the search for stable and functional
states of coordination,6it is possible that the greater variabil-
ity displayed by novice cyclists in the relative motion plots
of Fig. 1(b) of Chapman et al.1may represent exploratory
behaviour as the system attempts to discover stable regions
of the ‘perceptual-motor workspace’ or attractor states7that
subserve the production of functional, possibly optimal, coor-
dination solutions. The much narrower bandwidth of motor
variability exhibited by the expert cyclists could also be con-
sidered functional as it may represent subtle adaptations to
continuously fluctuating constraints on action, or ‘control-
lable chaos’ as Kelso and Ding8described it.
There are a number of theoretical and methodological
issues that need to be considered when attempting to estab-
lish the functionality and role of movement variability in
motor control and learning. First, operational analyses, such
as the one conducted by Chapman et al.,1need to be under-
pinned by a scientifically rigorous theoretical rationale that
should form the basis for hypothesis testing and experi-
mentation. Second, the theoretical framework adopted must
also have the scope to consider alternative interpretations
of motor variability, rather than making the default assump-
tion that it is an artefact of noise in the system.9Third, the
inverse relationship between movement variability and skill
level is not universally supported in the literature with some
studies actually showing reduced variability in less skilled
performers compared to their more highly skilled counter-
parts [e.g., 10,11]. Similarly, the clinical literature has shown
that patients exhibiting injury or disease, in some cases,
exhibit less variability than healthy controls12,13 although
there can be an increase or decrease of variability depending
on the intrinsic dynamics of the system and the constraints
on action.14,15 Finally, the recent introduction of non-linear
measurement tools16 in empirical studies have revealed that
it is the structure, rather than the magnitude, of movement
variability that appears to be of greater significance in under-
standing normal and pathological human perceptual-motor
functioning.17,18
To summarise, it is proposed that observations of motor
variability require careful consideration to establish its func-
tionality and role during goal-directed movement. Clearly,
the default interpretation that movement variability is syn-
onymous with noise is no longer tenable. However, this is not
to say that all motor variability is functional, but rather, that
not all variability is dysfunctional. Empirical research should
be firmly based on a theoretical framework, such as dynami-
cal systems theory, that can underpin hypothesis testing and
experimentation. Importantly, it is the structure, rather than
the magnitude, of variability that is important in uncovering
the functionality of this ubiquitous feature of human motor
behaviour.
1440-2440/$ – see front matter © 2009 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.jsams.2009.03.010
Letter to the Editor / Journal of Science and Medicine in Sport 12 (2009) e2–e3 e3
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Paul S. Glazier∗
Centre for Sport and Exercise Science, Sheffield Hallam
University, Collegiate Campus, Sheffield, UK
Keith Davids
School of Human Movement Studies, Queensland
University of Technology, Australia
∗Corresponding author.
E-mail address: paul@longdrivegolf.co.uk (P.S. Glazier)
13 February 2009
... It is proposed that, in becoming skilled, the system consolidates an 'attractor state' ensuring that the movement is performed consistently well while also developing the ability to adapt to changes in the constraints (Davids, Glazier, Araujo, & Bartlett, 2003;Glazier & Davids, 2009a;Seifert, Komar, Araújo, & Davids, 2016). ...
... Indeed, researchers have rejected the historic notion that the presence of variability in the motor patterns of skilled movers reduces the performance level. Rather, variability acts as a functional aid to performance in terms of offering different motor solutions to optimise kinematic patterns (Bartlett, Wheat, & Robins, 2007;Glazier & Davids, 2009a;Langdown, Bridge, & Li, 2012). For example, in the case of a basketball shot, the segmental rotations and positions of the shoulder, elbow, and wrist vary across trials, and yet they interact successfully to optimise the endpoint movement pattern (i.e. the trajectory of the hand: Button, Macleod, Sanders, & Coleman, 2003). ...
... * statistical significance (p < .05). experiment reflect the process of optimising performance through many pattern repetitions to develop, in terms of the dynamical systems perspective, deep and stable attractors suited to the behavioural dynamics of the task (Davids et al., 2003;Glazier & Davids, 2009a;Seifert et al., 2016). ...
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Before examining the effect of changing constraints on skill adaptation, it is useful to know the tolerable variability of a movement pattern for optimal performance. Tolerable variability may vary throughout the period of task performance as some parts of the movement pattern may be more important than others. The purpose of this study was to quantify the inter-trial variability of performance variables, and hand path as the task-relevant parameter, of skilled front crawl swimmers during 25 m sprints. It was hypothesised that the wrist paths would have smaller inter-trial variability during the below water phase than during the above water phase. Twelve skilled swimmers performed four 25 m front crawl sprints which were recorded by six phased locked video cameras for three-dimensional analysis. Standard deviations and time series repeatability (R²) of the right and left wrist displacement were determined. On average, swimmers varied their sprint speed between trials by <1.5%. The spatio-temporal patterns of wrist paths varied by <3 cm in all directions (horizontal, vertical & lateral). There was no significant difference in inter-trial variability between above and below water phases. Swimmers increased wrist path consistency at the critical events of water entry in the horizontal and lateral directions and at exit for the horizontal direction. This study established levels of variability in spatio-temporal movement patterns of the paths of the wrist in sprint swimming and provided evidence that swimmers minimise variability for key events, in this case, the position of the wrists at water entry and exit.
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... Cette perspective a ainsi entraîné des efforts visant à éliminer ou à réduire la présence de cette vi du mouvement. Toutefois, il est maintenant accepté que la vi du mouvement est inhérente au mouvement et que son étude permet d'en apprendre plus sur le fonctionnement complexe du système neuromusculaire (Glazier et Davids 2009 ;Latash, Scholz et Schöner 2002). ...
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... However, Glazier & Davids (2009) [66] state that it is the structure, ...
... However, Glazier & Davids (2009) [66] state that it is the structure, ...
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... With regard to the UEFA Champions League, it appears that the kinds and combinations of performance indicator disparities between successful and failing teams can matter more than the absolute values of such differences. The observation of this phenomena in this setting highlights similarities with previous research on human motor control and variation of movement (Glazier & Davids, 2009;Latash et al., 2002). Future studies could compare margin to win/loss (the metric employed in this study), as margin might provide a different viewpoint on performance than the binary result of win/loss (Sargent & Bedford, 2013;Stewart et al., 2007). ...
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... In fact, the above-referred incoherencies may be due to expertise, i.e., the ability to adapt to environmental or task constraints rather than reproducing a pre-determined motor pattern, giving insight into the technique in-between cycles, especially at maximal velocities (Seifert et al., 2016;Silva et al. 2019b). The inverse relationship between movement variability and experience is not fully acknowledged in the literature, with some studies showing reduced variability in less skilled performers compared to highly skilled counterparts (Ganzevles et al., 2019;Glazier & Davids, 2009). ...
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... In this study, no biomechanical data were acquired, which limits interpretation the observed outcomes. Furthermore, this study did not allow for an extensive familiarization period, which may explain the large variability in the outcomes [66], [67]. In this study the exoskeleton condition was compared to a condition without exoskeleton. ...
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... Also, the intra-and inter-individual variability of motor coordination and more generally of swimming technique would not be considered as an error with regard to the expert model, but as functional, i.e. a variety of behaviour and resources to be used by the teacher and coach to individualize and enrich their intervention (Davids, Glazier, Araújo, & Bartlett, 2003;. In sum, Adaptability means adapted and adaptive (or adaptable) behaviors: adapted behavior to a set of constraints reveals stability against perturbations, while adaptive or adaptable behavior reflects flexibility to guarantee functional solution to constraints that dynamically interact (Edelman & Gally, 2001;Glazier & Davids, 2009;Seifert et al., 2016). ...
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... An increased distance has been shown to instigate a reorganization of motor system dynamics. Constraints either allow individuals to explore the available phase-space [28], or alternatively, constrain the human movement system to a narrow range of kinematic solutions [29]. In other words, constraints set boundaries or limits within a dynamical system [30]. ...
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A Proposed Framework to Describe Movement Variability within Sporting Tasks: A Scoping Review
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Movement variability is defined as the normal variations in motor performance across multiple repetitions of a task. However, the term “movement variability” can mean different things depending on context, and when used by itself does not capture the specifics of what has been investigated. Within sport, complex movements are performed repeatedly under a variety of different constraints (e.g. different situations, presence of defenders, time pressure). Movement variability has implications for sport performance and injury risk management. Given the importance of movement variability, it is important to understand the terms used to measure and describe it. This broad term of “movement variability” does not specify the different types of movement variability that are currently being assessed in the sporting literature. We conducted a scoping review (1) to assess the current terms and definitions used to describe movement variability within sporting tasks and (2) to utilise the results of the review for a proposed framework that distinguishes and defines the different types of movement variability within sporting tasks. To be considered eligible, sources must have assessed a sporting movement or skill and had at least one quantifiable measure of movement variability. A total of 43 peer-reviewed journal article sources were included in the scoping review. A total of 280 terms relating to movement variability terminology were extracted using a data-charting form jointly developed by two reviewers. One source out of 43 (2%) supplied definitions for all types of movement variability discussed. Moreover, 169 of 280 terms (60%) were undefined in the source material. Our proposed theoretical framework explains three types of movement variability: strategic, execution, and outcome. Strategic variability describes the different approaches or methods of movement used to complete a task. Execution variability describes the intentional and unintentional adjustments of the body between repetitions within the same strategy. Outcome variability describes the differences in the result or product of a movement. These types emerged from broader frameworks in motor control and were adapted to fit the movement variability needs in sports literature. By providing specific terms with explicit definitions, our proposed framework can ensure like-to-like comparisons of previous terms used in the literature. The practical goal of this framework is to aid athletes, coaches, and support staff to gain a better understanding of how the different types of movement variability within sporting tasks contribute to performance. The framework may allow training methods to be tailored to optimise the specific aspects of movement variability that contribute to success. This review was retrospectively registered using the Open Science Framework (OSF) Registries (https://osf.io/q73fd).
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Identifying individual movement styles in high performance sports by means of self- organizing Kohonen maps
Conference Paper
Full-text available
  • Jan 1998
Introduction Although single case studies are common in more general oriented behavioral sciences (Yin 1988), they are still very rare in sports science. The lasting preference of group studies in sports science finds practical support in the opinion that by acquiring a system of reference values one will be provided with an ‚'optimal kinematic movement pattern' for every athlete at all levels of performance. Problems occur if the reference values are either considered as single independent variables or very often if the reference patterns are based on the performance of a best subject (Schmidt&Young 1991). A practical problem with such an approach arises by transfering the results to the training of an individual athlete in form of instructions (feedback), particularly, when we consider the disadvantageous effects of average feedback (Wulf/Schmidt 1996). Even if we have 'optimal training conditions' with individual feedback, common optimal movements as reference systems seem to be speculative considering the problem of causality not in a classical linear way but rather from a nonlinear point of view. In nonlinear systems, as most biological systems can be assumed as, small causes can have large effects and large causes can result in small effects. Whether the assumption of common achievable movement patterns is justifiable kinematically, is subject of this study with a pattern recognition approach. Methods The final throwing phase (app. 200ms) of 8 male and 19 female javelin throwers was filmed with two highspeed cameras threedimensionally. The male throwers were finalists of the world championship 1987 in Rome, whereas the female group consisted of 10 worldclass heptathletes and 19 javelin specialists with national and international level. From 2 female specialists 10 and 6 throwing trials were filmed respectively in different competitions. The throwers' movements were described by means of the time courses of the main joint angles and angular velocities. The joints at the ankle, knee, elbow, and head were assumed as planar and, the hip and shoulder joints were assumed as three dimensional. In addition the orientation angle of the trunk axis and its velocity was considered for a physically complete description. This results in a sequence of 51 (time-normalized) 34-dimensional feature vectors v i (t) per trial i. The data were further processed by normalizing the individual dimensions to a mean of 0 and variance of 1. We then trained the selforganizing Kohonen maps (SOM) to project the individual feature vectors to an N=7x6x6 neuron output space. Learning parameters were σ init = 4.0, reduced to σ final =0.2 during training, ε=0.9 à 0.01, 2x10 5 learning steps (Bauer/Schöllhorn 1997). The sequence of feature vectors v i (t) which constitute the original movement pattern is transformed by the SOM into a sequence of excited neurons r i (t). Instead of considering a distance between two feature vectors in the 34-dimensional input space (fig.1 left), we can now operate in the only 3-dimensional output space (fig.1 right), with all redundant, noisy extra dimensions suppressed.
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Harris, C. M. & Wolpert, D. M. Signal-dependent noise determines motor planning. Nature 394, 780−784
Article
Full-text available
  • Sep 1998
When we make saccadic eye movements or goal-directed arm movements, there is an infinite number of possible trajectories that the eye or arm could take to reach the target. However, humans show highly stereotyped trajectories in which velocity profiles of both the eye and hand are smooth and symmetric for brief movements. Here we present a unifying theory of eye and arm movements based on the single physiological assumption that the neural control signals are corrupted by noise whose variance increases with the size of the control signal. We propose that in the presence of such signal-dependent noise, the shape of a trajectory is selected to minimize the variance of the final eye or arm position. This minimum-variance theory accurately predicts the trajectories of both saccades and arm movements and the speed-accuracy trade-off described by Fitt's law. These profiles are robust to changes in the dynamics of the eye or arm, as found empirically. Moreover, the relation between path curvature and hand velocity during drawing movements reproduces the empirical 'two-thirds power law. This theory provides a simple and powerful unifying perspective for both eye and arm movement control.
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The Perceptual-Motor Workspace and the Acquisition of Skill
Article
  • Jan 1991
the acquisition of skill is examined with reference to the nature of the evolving perceptual-motor workspace / the evolution and dissolution of gradient and equilibrium regions within the workspace is [sic] discussed relative to the constraints on action / some experimental data are reported which address the impact of some of the features of perceptual-motor workspaces on exploratory behavior, criterion performance, and transfer while learning to locate the minimum of an unknown function (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Dynamics of skill acquisition: A constraints-led approach
Article
  • Jan 2007
This is an upper-level undergraduate or graduate textbook for courses in human movement and skill acquisition. A professional reference for movement practitioners and scientists, including teachers, coaches, physical educators, physical therapists, rehabilitation specialists, sport scientists, psychologists, biomechanists, and physiologists. The book provides a comprehensive analysis of the evolution of the constraints-led perspective, a recognized theory in motor learning and control. It outlines the development of a conceptual model of coordination and control within a multidisciplinary framework, capturing the various interlocking scales of analysis (e.g., neural, behavioral, psychological) and the many subsystems (e.g., perceptual and movement) involved in producing behavior. A conceptual model of coordination and control is important not just for designing learning environments, but it is also important for ensuring that learners gain positive experiences when acquiring motor skills. Practitioners and students will appreciate the applied focus which outlines a model of human movement with specific constraints-led approach strategies that address skill acquisition across a variety of professions, including teaching, coaching, and rehabilitation. By learning both the theoretical origins and applications for implementing a constraints-led approach to movement skill acquisition, readers will gain insight into how the informed organization of learning and rehabilitation environments produces more effective and efficient use of practice and therapy time. Contents: Traditional theories of skill acquisition -- Physical constraints on coordination : dynamical systems theory -- Informational constraints on coordination : an ecological perspective -- Redefining learning : a constraints-led approach -- Understanding the dynamics of skill acquisition -- Dealing with individual differences : implications for a nonlinear pedagogy -- Organizing practice to optimize learning -- Using verbal guidance as an informational constraint on learners -- Observational learning as directed search -- Implementing the constraints-led approach: case studies.
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A dynamical systems approach to lower extremity running injuries
Article
  • Jul 1999
  • CLIN BIOMECH
Unlabelled: In this paper, we are presenting an alternative approach to the investigation of lower extremity coupling referred to as a dynamical systems approach. In this approach, we calculate the phase angle of each segment and joint angle. Pairing the key segment/joint motions, we use phase angles to determine the continuous relative phase and the variability of the continuous relative phase. Data from two studies illustrate the efficacy of the dynamical systems approach. Individuals who were asymptomatic, even though they may have anatomical aberrant structural problems (i.e. high Q-angle vs low Q-angle) showed no differences in the pattern of the continuous relative phase or in the variability of the continuous phase. However, differences in the variability of the continuous relative phase were apparent in comparing individuals who were symptomatic with patellofemoral pain with non-injured individuals. Patellofemoral pain individuals showed less variability in the continuous relative phase of the lower extremity couplings than did the healthy subjects. We hypothesize that the lower variability of the couplings in the symptomatic individuals indicates repeatable joint actions within a very narrow range. Relevance: We claim that the traditional view of the variability of disordered movement is not tenable and suggest that there is a functional role for variability in lower extremity segment coupling during locomotion. While the methods described in this paper cannot determine a cause of the injury, they may be useful in the detection and treatment of running injuries.
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