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C U R R E N T O P I N I O N Open Access
Smoothness: an Unexplored Window into
Coordinated Running Proficiency
John Kiely
1*
, Craig Pickering
1,2
and David J. Collins
3,4
Abstract
Over the expanse of evolutionary history, humans, and predecessor Homo species, ran to survive. This legacy is
reflected in many deeply and irrevocably embedded neurological and biological design features, features which
shape how we run, yet were themselves shaped by running.
Smoothness is a widely recognised feature of healthy, proficient movement. Nevertheless, although the term
‘smoothness’is commonly used to describe skilled athletic movement within practical sporting contexts, it is rarely
specifically defined, is rarely quantified and remains barely explored experimentally. Elsewhere, however, within
various health-related and neuro-physiological domains, many manifestations of movement smoothness have been
extensively investigated. Within this literature, smoothness is considered a reflection of a healthy central nervous
system (CNS) and is implicitly associated with practiced coordinated proficiency; ‘non-smooth’movement, in
contrast, is considered a consequence of pathological, un-practiced or otherwise inhibited motor control.
Despite the ubiquity of running across human cultures, however, and the apparent importance of smoothness as a
fundamental feature of healthy movement control, to date, no theoretical framework linking the phenomenon of
movement smoothness to running proficiency has been proposed. Such a framework could, however, provide a
novel lens through which to contextualise the deep underlying nature of coordinated running control. Here, we
consider the relevant evidence and suggest how running smoothness may integrate with other related concepts
such as complexity, entropy and variability. Finally, we suggest that these insights may provide new means of
coherently conceptualising running coordination, may guide future research directions, and may productively
inform practical coaching philosophies.
Key Points
Smoothness is a universal feature of healthy skilled
movement which, although infrequently considered
and currently under-appreciated within sporting
contexts, may provide a unique window into athletic
coordinative proficiency.
Existing evidence illustrates that smoothness
changes as a consequence of natural aging, general
health status, practice and injury history and current
fatigue and injury status. Preliminary research
suggests that running proficiency is reflected in
smoother running movement.
Recent advances in wearable technologies provide
the opportunity to sensitively detect changes in
running smoothness, thereby potentially bestowing
unique insights into running coordination
proficiency
Introduction: What Do Running Proficiency and
Hard-Core Pornography Have in Common?
During his tenure as a US Supreme Court justice, Potter
Stewart presided over many high profile cases. He, for
example, promoted personal privacy protections and ex-
tended the 1866 Civil Rights Act to concede that schools
should not discriminate on the basis of race. Outside of
legal contexts, however, he is best remembered for a sin-
gle clause, from a single sentence. While adjudicating on
the legality of the state of Ohio’s banning of an allegedly
pornographic film, Stewart uttered perhaps the most
famous phrase in the Supreme Court history, ‘I shall not
today attempt further to define the kinds of material I
understand to be embraced within that shorthand de-
scription [“hard-core pornography”], and perhaps I could
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made.
* Correspondence: jkiely@uclan.ac.uk
1
Institute of Coaching and Performance, School of Sport and Health
Sciences, University of Central Lancashire, Preston, UK
Full list of author information is available at the end of the article
Kiely et al. Sports Medicine - Open (2019) 5:43
https://doi.org/10.1186/s40798-019-0215-y
never succeed in intelligibly doing so. But I know it
when I see it …[1]’In this context, ‘I know it when I see
it’is a euphemistic abstraction describing a phenomenon
that—by virtue of its apparent ‘obviousness’—is simul-
taneously familiar to all, yet surprisingly difficult to char-
acterise, quantify or elegantly articulate.
The topic explored in this article, we suggest, shares
these features in that although, superficially, it appears
intuitively obvious and readily apparent; when we at-
tempt to explain exactly what ‘it’is, we find that beneath
this facade of familiarity lies a phenomenon that remains
inadequately defined and poorly understood.
What Is Movement Smoothness?
Across a diversity of literatures, and within practical
coaching contexts, movement smoothness is generally
recognised as a universal feature of skilled motor behav-
iour [2]. Yet, despite this assumed association between
movement smoothness and movement proficiency,
current definitions of smoothness remain surprisingly
vague. A recently proposed definition suggests that a
movement is perceived to be smooth when it happens in
a continual fashion without any interruptions, suggesting
smoothness is a quality reflecting the continuality or
non-intermittency of movements that alternately accel-
erate and decelerate, and thereby remains independent
of amplitude and duration [3]. In this context, more
intermittency corresponds to less smoothness, and less
intermittency to smoother movement.
The minimum-jerk model, first proposed by Flash and
Hogan, suggested that human movement is executed in
a manner that optimises smoothness by minimising its
opposite, kinematic jerk [4]. Although smoothness can
be assessed in multiple ways—a recent review suggests
at least eight methods have been used in research con-
texts—the most common means of assessing smoothness
is through the quantification of jerk [3]. Jerk is formally
defined as the rate of change in acceleration, in mathem-
atical terms, the first time derivative of acceleration, the
second time derivative of velocity and the third time de-
rivative of position [4,5]. The smoothest movements
consequently have, by definition, the lowest jerk [6]. Ac-
cordingly, within the neuroscientific literature, smooth
movement has been described as any movement that is
not ‘jerky’[7].
From a practical coaching perspective, however, we can
sensibly broaden this definition by proposing that smooth
movements are those without abrupt, intermittent, dis-
continuous changes in accelerations, relative joint posi-
tions and/or movement trajectories. Accordingly,
although movements may occur rapidly, unexpectedly,
even violently, there is a sense of consistent flow, of finely
regulated progression and seamlessly continuous coord-
inative control. Thus, key dimensions of movement—
postural control, relative joint positions, the absorption of
impacts—all appear to rhythmically and incrementally rise
and fall. Visually, accordingly, we register a sense of flu-
ency as the athlete dynamically progresses through a given
movement sequence. Non-smooth movements, in con-
trast, leave an impression of abruptness, of erratic discord-
ance and of disjointed, unpredictable control.
Smoothness seems intuitively recognised as a hallmark
of skilled, coordinated movement [8]. Nevertheless, in
relation to sporting movements in general, and running
specifically, although the term ‘smoothness’is commonly
used to describe performer’s movement ability, it is
rarely defined, is rarely empirically quantified, is barely
explored academically and is typically not directly tar-
geted in training. In short, running smoothness is a
phenomenon that we instinctively ‘feel’we recognise
when watching elite performance. Yet, beyond this intui-
tive recognition, exactly what smoothness is remains
surprisingly vague. Thus, just as Potter Stewart struggled
to eloquently articulate the essence of a phenomenon as
superficially self-evident as pornography, we similarly
struggle to accurately characterise a dimension of move-
ment as seemingly obvious as smoothness.
Notably, recent advances in accelerometer technology
now provide access to raw, unfiltered acceleration time
series that can readily be converted to jerk data. Surpris-
ingly, however, this research topic has received very little
attention within sports science contexts. In attempting
to enhance our appreciation of this potentially import-
ant, yet largely ignored phenomenon, here, we examine
the general evidence relating to movement smoothness,
before subsequently reflecting on how these insights
may contribute to a more robust understanding of run-
ning coordination.
The Progression and Regression of Movement
Smoothness
Smoothness increases progressively as we transition
from infant, to developing child, to mature adult, and re-
gresses as we move from adult maturity into old age [9–
11]. Furthermore, smoothness—whether assessed in
gross movements or fine motor skills—improves, in
logarithmic fashion, in parallel with the number of prac-
tice trials performed [12,13]. This effect is such that
practice-driven improvements are reflected in increased
smoothness in movement tasks as diverse as walking
[13], writing [14], rock climbing [15], driving a golf ball
[16], piano playing [17], wheelchair propulsion [18], dan-
cing [19], over-arm throwing [20] and in the hand dex-
terity of surgeons [21,22].
Many dimensions of declining function are, conversely,
reflected in the deterioration of movement smoothness.
Most obviously, smoothness is compromised following
neurological damage, such as stroke, and subsequent
Kiely et al. Sports Medicine - Open (2019) 5:43 Page 2 of 9
recovery is typified by the gradual restoration of
smoother movement [13]. This effect is such that even
simple measures of smoothness—evaluated in sit-to-
stand tests, for example—can distinguish between older
adults at risk of falls, older adults who are not a falls risk
and younger adults [23,24]. Similarly, smoothness dur-
ing lifting movements—assessed at hip and ankle—de-
clines with advancing age [25], and many disease states,
such as Parkinson’s and Huntington’s, are accompanied
by deteriorating smoothness [26]. Furthermore, in chil-
dren, developmental disorders such as autism and
Asperger’s are typified by a lack of movement smooth-
ness [27], and smoothness measures accurately detect
delayed motor skill acquisition [8].
Additionally, smoothness measures can discern be-
tween those who have previously suffered cervical injury
and non-previously injured controls [28], between those
feigning whiplash injury and sincere patients [29] and
between wheelchair users with, or without, shoulder
pain [18]. Smoothness assessments are also sufficiently
sensitive to detect decrements in highly learned skills
caused by, for example, the influence of distractions on
the driving performance of experienced taxi drivers [30]
and movement skill inhibition following emotional dis-
turbances [31].
Why Is Smoothness a Universal Feature of Human
Movement?
Several theories of motor control hypothesise that the
brain coordinates muscle activation patterns to minimise
a single, task-relevant cost function. Historically, it was
assumed that the most heavily prioritised cost function,
shaping movement control, was energetic expenditure
[32]. Recent investigations, however, clearly demonstrate
that although energy conservation is unquestionably a
consideration, it is neither the only, nor necessarily the
dominant, cost function shaping motor behaviours [32,
33]. Modelling predictions, for example, illustrate that
‘impulsive running’—running with infinitely stiff, straight
legs and zero sweep angle—minimises the mechanical
cost of transport [34]. Nevertheless, we run with ener-
getically costly, compliant legs in a manner deviating
substantially from this hypothetical optimum [35]. In
fact, energy conservation appears to be only one of a
growing list of proposed constraints, each capable of ad-
equately predicting the common kinematics of human
movement. Such considerations include, for example,
preservation of stability, reductions in the neural ‘effort’
expended in controlling movement, the minimisation of
changes in torque, the minimisation of discomfort and
the regulation of movement accuracy [3,36,37]. Thus,
although practiced movements are typically executed in
a manner that reduces energy costs, energy expenditure
is not an exclusively over-riding priority and is certainly
not minimised. Although, experimentally, it seems im-
possible to determine which cost function is most heav-
ily prioritised by the brain, notably, models prioritising
smoothness consistently produce high-performing pre-
dictions [3,33,34].
Nevertheless, although various rationales have been
proposed within the relevant literatures, the reasons why
smoothness is such a fundamental feature of healthy
movement remain unclear. Previous research suggested
that smoothness, during ground contact events, is an in-
direct consequence of the CNS’s preference to employ
single activation signalling bursts to individual muscles
[38]. The authors speculated that this strategy enabled
adequate outcomes, while greatly simplifying neural con-
trol complexity. Furthermore, the authors noted they
could see no reason why smooth movements offered ad-
vantages over non-smooth ones. Their proposal, instead,
was that smoothness evolves naturally from the interplay
between a single-stimulation-burst-per-muscle activation
pattern, the linear behaviour of the leg spring and the in-
nate viscoelastic and geometric properties of the muscu-
loskeletal system. In essence, suggesting smoothness, in
landing tasks, emerges as a by-product of an evolution-
ary preference for simplified neural control, rather than
because smoothness, in and of itself, offers any add-
itional benefits [38].
More recent work, however, has proposed that smooth
movements are inherently more predictable than less
smooth, more erratic ones [39]. A more accurate predic-
tion of upcoming movement demands is of substantial
benefit as it permits a more fine-grained alignment be-
tween forecasted demands, advance preparation to meet
these demands and actually imposed demands [39]. En-
hanced predictive accuracy, accordingly, facilitates a
more precisely attuned—more timely and more finely
calibrated—preparation for impending challenge. Ac-
cordingly, it is suggested that smoothness, as it promotes
predictability, minimises movement error [39–41]. Simi-
larly, more sensitive detection of subtle deviations from
predicted trajectories facilitates more sensitive remedial
adjustments, thereby offsetting the need for periodic, lar-
ger, more disruptive and energetically demanding cor-
rective interventions [42].
Non-smooth (by definition, more jerky) movements, in
contrast, are inherently less predictable [41]. This dimin-
ished predictability inevitably detracts from the accurate
forecasting of the likely kinetic and kinematic conse-
quences of upcoming ground contacts [43]. Any loss of
calibration between anticipated and actually imposed de-
mands inevitably leads to larger deviations from ex-
pected trajectories, thereby requiring more drastic
remedial interventions to ‘correct’unwanted deviations
[39]. Larger corrective interventions necessitate larger
motor commands, which generate, as a natural by-
Kiely et al. Sports Medicine - Open (2019) 5:43 Page 3 of 9
product, more signal-dependent neural noise, thereby
further diminishing movement proficiency [43]. Conse-
quently, previous evidence has been interpreted as sug-
gesting that humans strive to optimise smoothness and
minimise jerk [41].
In summary, more precise predictability facilitates a
finer calibration between current preparation for soon-
to-be-imposed demands and the likely extent of those
challenges. Smooth movements, as they require smaller
on-line course corrections, minimise the disruptive ef-
fects of signal-dependent noise emerging as a natural
consequence of larger motor commands [39]. Conse-
quently, in a mutually re-enforcing manner, smoothness
enhances prediction and prediction enhances smooth-
ness. Smoothness, accordingly, by facilitating improved
prediction, minimises the necessity of persistent remed-
ial correction and thus serves to, simultaneously, reduce
both the neuronal computational burden associated with
complex movement and energetic expenditure [3,39,
40].
The Foundations of Movement Smoothness
Locomotion is initiated by commands originating in the
motor cortex [42]. These descending commands are me-
diated and modulated by control centres in mid-brain
and brain stem, before subsequently activating spinally
located central pattern generating (CPG) networks re-
sponsible for controlling the rhythmic synchronisation
of the arms and legs, thereby delegating much of the co-
ordination burden to lower, less evolutionarily expensive,
neural control centres [42]. As rhythmic locomotion
progresses, streams of sensory feedback return to spinal
centres and serve to (a) guide the on-going
customization of CPG outputs to current contexts and
(b) trigger stabilisation reflexes [42]. Through these
mechanisms, sensory feedback directly alters on-going
feedforward activation, and changes in activation in-
escapably alter changes in sensation. These feedback and
feedforward loops are so inseparably entwined that
representing them as isolated entities seems no longer
sensible. Instead, feedback and feedforward information
flows are best perceived as wholly integrated, mutually
modulating arms of the sensorimotor system [36,37].
Inevitably, however, neural and reflex-activating feed-
back and feedforward loops take time and cannot in-
stantaneously respond to imposed perturbation.
Proficient execution of impact-dependent movements—
walking, running, jumping—thus requires that the earli-
est remedial compensations, upon ground contact, are
mediated by the practiced manipulation of the intrinsic
material and structural properties of biological tissue
collectives [41,42,44]. When skillfully deployed, the in-
nate viscoelastic and geometrical properties of the run-
ning leg provide an instantaneous, non-neurological, yet
skilled, response to impact perturbations (for little ener-
getic and neurological investment) [41,42]. Thus, in-
formed by anticipation and actioned by feedforward
instruction, the time-lag deficits implicit in top-down
neurally mediated motor control are offset by the skilled
manipulation of biological tissue properties [42,45].
Rhythmic locomotion, accordingly, is regulated by the
blended output of three distinct, but mutually and irrev-
ocably entangled, levels of control:
1. Top-down, supra-spinal executive direction
2. Spinally located CPGs and stabilisation reflexes
3. The bottom-up, self-stabilising capacities afforded
by the innate perturbation-resilient characteristics
of bio-composite tissue structures [41]
When operating effectively, feedback and feedforward
information is blended with the plastically embedded
legacy of prior experience, to facilitate the skilled deploy-
ment of robust, task-conditioned, bio-composite tissue
capacities. The fusion of these multi-level control sys-
tems underpins the runner’s ability to sensitively detect
and respond to upcoming perturbations in ways that
minimally disrupt rhythmical locomotion. Smoothness
thus emerges as a natural outcome of this intimate inte-
gration between accurate anticipation of upcoming per-
turbations and the advance remediation of forecasted
de-stabilisations [46,47].
Is Movement Smoothness an Important Feature of
Running?
Within a number of academic literatures, smoothness is
acknowledged as a fundamental characteristic of goal-
directed human movement [3,48]. Although not well in-
vestigated within sporting contexts, preliminary evidence
suggests smoothness measures are capable of discerning
between different levels of expertise. The clubhead tra-
jectories of skilled golfers, for example, are smoother
than those of unskilled golfers [49]. Recent research, fur-
thermore, established that a lack of smoothness—in the
postural sway adjustments of NCAA Division 1 College
football players—predicted the likelihood of subsequent
injury [50]. Such findings suggest smoothness is a
phenomenon reflecting both practice-related skill im-
provements and the underpinning functional health of
the neuro-muscular system.
Specifically, in relation to running, however, empirical
insights remain sparse. An early study, by Hreljac, used
video analysis techniques to determine runner’s jerk-cost
at ground contact and established that competitive run-
ners ran more smoothly than recreational runners [12].
Subsequently, Cortes and colleagues, using trunk-
mounted sensors to collect acceleration data during a
running-and-cutting maneuver, illustrated that fatigue-
Kiely et al. Sports Medicine - Open (2019) 5:43 Page 4 of 9
induced changes in motor variability detracted from the
smooth execution of the target movement [51].
Running Smoothness and the Loss of Complexity
Hypothesis
In 1992, Lipsitz and Goldberger published an influential,
and much cited, JAMA paper proposing the loss of com-
plexity hypothesis, suggesting that, as we age, the com-
plexly intertwined neural and biological foundations,
which support all essential neurophysiological processes,
gradually and progressively degrade [52]. Through this
conceptual lens, reductions in complexity are indicative
of declining neurophysiological responsiveness and
adaptive range [52–54]. Interestingly, a limited number
of recent investigations, using measures of entropy—a
means of analysing the complexity inherent in a data
time series—have demonstrated that running-induced
fatigue changes the complexity of the acceleration sig-
nals emanating from sensors attached to a site approxi-
mating centre of mass (CoM) [55–57].
Translating the loss of complexity hypothesis to run-
ning contexts suggests that reductions in underlying
neurobiological complexity diminish the spectrum of vi-
able movement permutations capable of equitably pro-
viding equivalent stride outcomes for a comparable
‘cost’. Accordingly, changes in signal complexity are
interpreted as reflecting a contracting range of available
micro-movement permutations capable of collabora-
tively solving the running-imposed challenge [54]. Con-
sequently, as complexity contracts, the inter-stride
variability inherent in each runner’s stride pattern is im-
pelled to dysfunctionally diverge from habituated norms
[54,58,59]. This divergence, in turn, is hypothesised to
expose the runner to both declining movement effi-
ciency and exacerbated risk [51,58,59].
The relevance of this rationalisation, to the topic of
running smoothness, is to suggest that diminishing
neurobiological complexity—induced, for example, by fa-
tigue, prior injury, pain sensitization and/or age-related
decline—drives deteriorating coordinative control and
the subsequent erosion of running smoothness [54,58,
59]. As encapsulated within the loss of complexity hy-
pothesis, the inevitable accumulation of experience-
dependent wear and tear—associated with natural aging,
declining health and injury and illness—progressively
erodes both tissue micro-architectures and the connect-
ive integrity of densely entangled neural communica-
tions networks. Any subsequent reduction in neural
communicative clarity—driven, for example, by injury,
sensitization and/or residual fatigue—inevitably dims the
runner’s fine-grained perception of their precise kine-
matic and kinetic context. (Although research in this
realm remains sparse, prior injury has been observed to
erode the proprioceptive capacities of elite runners and
ballet dancers [60,61]).
As a direct consequence, this diminished sensorimotor
capacity impedes optimal preparation for upcoming
ground contact and detracts from the sensitive calibra-
tion of running stiffness to the precise demands of the
impact challenge [54,59]. Consequently, reduced sen-
sorimotor sensitivity directly diminishes coordinated
control and can be expected to increase the magnitude
of unexpected deviations from projected trajectories,
thereby suggesting that diminished proprioception dir-
ectly impedes activation precision and degrades move-
ment smoothness [62–64]. Specifically, in running
contexts, it has recently been suggested that the gradual
degradation of available complexity is compounded by
cycles of overuse, underuse, misuse and disuse [54,65].
As complexity contracts, running coordination inevitably
declines, and running smoothness deteriorates. Although
the exact mechanisms underpinning this progressive de-
terioration remain unclear, two broad inter-related
neuro-motor deficits have been implicated:
i. As the plastically embedded legacies of past cycles
of injury, misuse, disuse and overuse accumulate
within the CNS, the micro-structures underpinning
neuronal connectivity progressively degrade, and
available complexity contracts [54,58,59]. Conse-
quently, sensorimotor communication clarity
erodes, and both the interpretation of sensory feed-
back and the precision of feedforward activations
gradually decay.
ii. Declining muscular strength—driven by neural
signalling decrements, decreasing muscle mass and
the degradation of tissue micro-
structures—necessitates that, to adequately execute
a task requiring a given movement force, weaker
muscles require more relative activation, and hence
larger activation signals than stronger muscles [54,
66]. Inevitably, larger relative activations result in
increasing neural noise, thereby resulting in more
disorderly motor unit recruitment and more erratic-
ally variable force outputs.
As multiple aspects of sensorimotor control—sensory
acuity, activation accuracy and the load management
capacity of biological tissues—erode, subsequent to the
accumulating legacy of past insults, underlying complex-
ity inevitably deteriorates. Accordingly, the spectrum of
available coordinative responses to running-imposed
mechanical challenges declines [67,68]; consequently,
smoothness declines. Although this proposed causal
chain—linking neurobiological complexity, entropy, vari-
ability and running smoothness—appears theoretically
robust, and has been observed in other movement
Kiely et al. Sports Medicine - Open (2019) 5:43 Page 5 of 9
contexts, it remains barely explored and has not been
validated within human running applications [69].
Future (Practical and Research) Directions?
Conceptually, smoothness seems an important facet of
proficient running and a potential sensitive indicator of
injury or fatigue-induced running deterioration. Clearly,
however, evidence is lacking and the topic remains
under-explored. We can, however, draw some specula-
tive, but logical, initial conclusions:
1. Smoothness is modified by a range of factors,
including:
a. Underlying health status (including neuro-
physiological, psycho-emotional and disease
status)
b. Training and injury history
c. Current fatigue and/or psycho-emotional states
2. Smoothness progresses and regresses as a function
of normal maturation and aging, injury and
subsequent recovery, and declining smoothness
exposes tissues to exacerbated mechanical stress
3. Smoothness is a product of proficient coordination,
mediated by the CNS, and actioned via the skilled
deployment of the innate perturbation-resilient cap-
acities of robust biological tissues
Given the recent evolution and current ubiquity of
lightweight and sensitive accelerometer sensor technol-
ogy, the evidence and rationalisations provided here also
point towards potentially fruitful future research direc-
tions, highlighting, for example:
1. The opportunity to more fully explore the
associations between fatigue, prior injury and
running smoothness
2. The prospect of analysing acceleration time series
using entropy-based techniques to better illuminate
the hypothesised relationships between complexity,
inter-stride variability, running proficiency and
prior injury profiles
3. The proposition that enhanced accelerometer
technology, entropy analysis techniques and the
current availability of extensive computational
capacity all suggest that we may be on the
threshold of a transformation in how we
conventionally devise, prescribe and monitor fatigue
within running training contexts
Specifically, in relation to targeting running smooth-
ness within training design and prescription contexts,
beyond the general observation that running practice—
under healthy, non-fatigued conditions—appears to en-
hance smoothness, there are no specific evidence-led
guidelines. Speculation based on the sparse existing evi-
dence does, however, hint that while practice improves,
excessively repetitive practice leads to deteriorating
neural communications and declining movement
smoothness [42,54]. Accordingly, more volume is not
necessarily better. Instead, as with other facets of train-
ing management, improving running smoothness likely
requires the sensitive regulation of volumes, intensities,
exercise variation and the judicious balancing of work
and recovery.
From a conditioning perspective, again, evidence is
lacking and once more we are limited to theory-based
speculation. Building on the rationale presented here,
and elsewhere [54], we suggest smoothness is promoted
by three broad categories of training intervention:
1. Engaging in the simple act of running at a range of
paces and/or at target race pace under healthy,
non-fatigued and non-sensitised conditions
2. Engaging in running-related challenges promoting
an enhanced calibration between feedforward acti-
vation and proprioceptive information by providing
non-habituated, coordination challenges capable of
stimulating neuro-plastic re-modelling processes
serving to refine communicative clarity between
CNS and the peripheral musculature [54,70,71]
3. Engaging in training strategies serving to upgrade
the structural and material resilience of biological
tissues habitually subjected to mechanical stress
during running activities [41], for example,
resistance loading strategies [72], and/or strategies
promoting more finely calibrated joint control, for
example, dynamic stability challenges [73–75]
Conclusion
Smoothness is a product of the collaborative triangula-
tion between accurately interpreted sensory feedback
and sensitively adjusted feedforward activation, contex-
tualised against plastically embedded prior learning. As
physical capacities and movement experiences accumu-
late, we innately gravitate towards smoother movement
solutions as we learn to more sensitively respond to
small perturbations, thereby offsetting the need to peri-
odically and ‘jerkily’respond to the larger challenges that
would emerge if minor errors were allowed to accumu-
late. Smoothness thus reflects sensorimotor coordination
and provides a quantifiable window into movement pro-
ficiency [5].
The rapid evolution of wearable micro-technology
provides us with opportunities to accurately, and non-
invasively, evaluate running smoothness. Currently, how-
ever, although evidence strongly suggests smoothness
metrics provide insights into coordination proficiency,
and can be used as markers of neuro-rehabilitation
Kiely et al. Sports Medicine - Open (2019) 5:43 Page 6 of 9
effectiveness, the most appropriate means to measure,
monitor and analyse smoothness remain unclear [3,48].
And so, just as Potter Stewart struggled to eloquently
articulate the essence of a phenomenon as superficially
self-evident as pornography, within both practical and
theoretical running contexts, we similarly struggle to de-
fine and describe a phenomenon as intuitively familiar,
yet as seemingly important as running smoothness. Al-
though preliminary evidence demonstrates the informa-
tional value of smoothness assessments, such measures
exist only on the periphery of our sporting cultural con-
sciousness and remain poorly articulated, poorly under-
stood and poorly explored.
Pornography may forever remain subjectively ambigu-
ous and objectively unquantifiable, but that need not be
the case with running smoothness. Yet, as discussed, an
evidence-led logic supports the potential worth of ob-
jective smoothness evaluations, and currently, there is
ready access to technologies enabling such evaluations.
And while, unquestionably, much remains to be clarified
and further research is (as always) necessary, the back-
ground and rationale outlined here serves as a useful
conceptual starting point from where to begin this
exploration.
Acknowledgements
Not applicable.
Authors’Contributions
JK designed and wrote the manuscript. CP and DC provided critical editorial
comment and feedback. All authors have read and approved the final
manuscript.
Authors’Information
JK is a former International Boxer, Head of Strength & Conditioning at UK
Athletics, and currently a Senior Lecturer in Elite Performance at the Institute
of Coaching & Performance, University of Central Lancashire, UK.
CP is a former Olympic sprinter and Winter Olympian undertaking a
Professional Doctorate in Elite Performance at the Institute of Coaching &
Performance, University of Central Lancashire, UK. He is currently the Athlete
Pathway Manager for Athletics Australia.
DC is a former Performance Director of UK Athletics and is currently a
performance psychology consultant and Professor at the University of
Edinburgh, UK.
Funding
No sources of funding were received to support the preparation of this
article.
Availability of Data and Materials
Not applicable.
Ethics Approval and Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Competing Interests
The authors, John Kiely, Craig Pickering, and David J. Collins, declare that
they have no competing interests.
Author details
1
Institute of Coaching and Performance, School of Sport and Health
Sciences, University of Central Lancashire, Preston, UK.
2
Athletics Australia,
Brisbane, Queensland, Australia.
3
Grey Matters Performance Ltd., Birmingham,
UK.
4
Moray House School of Education and Sport, University of Edinburgh,
Edinburgh, UK.
Received: 28 January 2019 Accepted: 12 September 2019
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