Conference PaperPDF Available

Movement Variability: Science and Practical Application

Authors:
1
Movement Variability – Science
And Practical Application
Guido Van Ryssegem.
Safe Recovery, LLC, Corvallis, Oregon,
USA
Abstract
In the last 20 years concepts related
to the dynamic systems theory have
influenced the way we think about
movement, movement variability and noise
or error of data. Variability in movement is
a natural and normal phenomenon that
influences our lives, our physical
accomplishments and our health. Motor
skills in the healthy populations are
associated with an optimal amount of
movement variability, while in the
unhealthy populations motor skills are less
than optimal. As exercise is prescribed as
an intervention, a clear understanding on
what movement variability is, how it gets
influenced and how it can be manipulated
should be a priority so audiences’ goals can
be met.
This paper reviews the literature
related to movement variability in the
human adult, what its relationship is to
performance, what its relationship is to
injury, how this variability impacts different
populations and how the concepts related to
movement variability can be manipulated
so performance or return to performance
can be improved. Exercise
recommendations are being brought
forward for these populations. This paper
does not cover the theoretical background
of movement variability, the relationship
between movement variability and child
development nor is the focus on how
movement variability is measured.
Key Words: dynamic systems
theory, movement variability, variability,
performance
INTRODUCTION
Human movement variability has been
recognized as the normal variations in
motor skill acquisition across multiple
repetitions of a task (1) (2) (3). Variability
is inherent to movement and can easily be
observed when learning a new task. Until
recent, movement variability was attributed
to random error or noise in data and was
thereby mostly ignored (4) (5) (6) (7) (8).
Others suggested that movement variability
is not entirely random, and accordingly,
contains important data and information (1)
(9) (10).
It is speculated that in a more practical
sense, movement variability can be
described as the amount of variability
present within the entire neuromuscular
system while performing a specific task.
This can then provide an individual with the
capability of adapting to a variety of
challenges (2). These challenges include
changes in the biological system, (i.e. the
body), the environment, and the task
constraints in order to produce a more
consistent pattern when performing the
same movement (11). The author suggests a
systematic approach, manipulating these
three constraints to augment performance or
return to performance after injury.
Numerous studies found a relationship
between movement variability and
performance as well as a relationship
between movement variability, injury and
health. Although some variability is
required in order to be effective in a variety
of circumstances, too much or too little may
lead to a decrease in performance (12) (13)
and increases one’s susceptibility to injury
(14).
2
Perspectives on Movement Variability
A variety of perspectives on movement
variability have been published in the
scientific literature. Variation in a given
movement pattern has been considered by
some as the result of errors. Task-specific
practice gradually eliminates these errors,
optimizing the accuracy and efficiency of
the challenged movement pattern (15) (16).
Davids, K. suggests (17) that elite
performance is often characterized by low
variability of outcomes (18) as their motor
performances are characterized by highly
consistent patterns of movement. Many
assume that people share a common
optimal pattern of movement and that there
is a single most efficient and effective way
of performing it (19). Therefore, motor
variability has been considered being a
problem in the sensorymotor system that
should be minimized or eliminated (4) (5)
(6). Also, sports biomechanists and
movement coaches often make the
assumption that sport performances are
associated with optimal patterns of
movement execution, believing that there is
a single most efficient and effective way of
performing a skill at the elite level. They
believe that this elite performance should
then be copied by others (19). These
assumptions may have contributed to the
negative connotations of human movement
variability.
Zazone, et al. suggested that from a
dynamic systems perspective, biological
systems like the human body self-organize
to find the most stable solution when
moving (20) (21) (22). If so, then decreased
variability generally indicates highly stable
and cooperative behavior and increased
variability is the opposite. Optimal
variability is said to lie between these two
limits (23). Thereby movement variability
needs to be carefully interpreted in
relationship to the task at hand and not be
dismissed as not being important. When the
sensorymotor system adopts a functionally
preferred state of coordination, the capacity
of the system to produce consistent and
stable patterns of coordination is considered
ideal (24) (25). Also a flexible and
adaptable sensorymotor system can adapt
into optimal states of coordination when
exposed to environmental and task demands
(26). Numerous studies suggest that this
movement variability is an essential feature
of human motor behavior as it affords the
necessary flexibility and adaptability to be
successful in a variety of performances (16)
(22) (27) (28) (29) (30) (31) (32).
Recently, Stergiou, et al. (23) proposed a
new model on movement variability and
how it relates to health and motor learning.
Their perspectives are based on the idea
that mature motor skills and healthy states
are associated with an optimal amount of
movement variability, reflecting the
adaptability of the body as a system. Less
than optimal movement variability
characterizes systems that are overly rigid
and unchanging, whereas greater than
optimal variability characterizes systems
that are noisy and unstable. Both situations
characterize systems that are less adaptable
to challenges, typically associated with the
unhealthy. Thus, stable yet adaptable
systems maintain a rich repertoire of
movement strategies containing optimal
variability. They also then suggest that
interventions should foster the development
of this optimal amount of movement
variability by incorporating a rich repertoire
of behavioral strategies. Promoting
complex variation in human movement
allows either motor development or the
recovery of function after injury through
active engagement of the individual within
their environment.
3
Movement Variability and Performance
Movement variability has a functional role
in motor behavior. Recently, dynamic
systems based research supports that
movement variability is an essential feature
of motor behavior that affords the
sensorymotor system the necessary
flexibility and adaptability to operate
proficiently in a variety of performances
(16) (22) (27) (28) (29) (30) (32).
The amount of variability present within the
neuromuscular system changes as
individuals learn the movement patterns
necessary to perform a skill. During the
initial stages of learning a skill, typically
there is a tendency to produce very stiff and
seemingly uncoordinated movements (33).
As individuals become more comfortable
with the movement associated with the new
skill, they begin to appear more fluid and
coordinated. Once individuals master a
skill, the amount of variability present in
one’s performance may remain stable or
may change across multiple repetitions of a
given task (34). Although some variability
is required in order to be effective, too
much or too little may lead to a decrease in
performance (12) (13).
The amount of coordination variability
present within the neuromuscular system
should reach a level of stability as
individuals learn a given task (13).
Untrained and skilled individuals have
different levels of coordination variability
across different skills. The untrained show
greater variability than skilled performers
when bouncing a basketball (35) and
playing handball (36). In other studies,
untrained and highly skilled performers
have shown more coordination variability
than those with intermediate skill level in
the triple jump (13). According to Wilson et
al., as participants learn a skill, the amount
of coordination variability present within
the neuromuscular system undergoes a U-
shaped pattern. While novices have high
coordination variability due to the
neuromuscular system being highly
unstable, experts have high coordination
variability due to their ability to adapt to
change (13).
Already in 1968 and 1969, Arutyunyan, et
al. (37) (38) found that skilled marksmen
showed reduced variability in the
orientation of the pistol barrel when aiming.
In contrast, the novice marksmen exhibited
greater variability, not able to optimally
control the task. In serving, consistency in
ball placement during the toss phase can
facilitate success in tennis, volleyball as
also in badminton, squash, table tennis and
racquetball (39) (40). The study on serves
(40) clearly demonstrated that practicing
ball tossing should emphasize the
development of a stable peak height in
favor of consistency in the other directions.
Studies on triple jumpers (13) showed that
initially high variability was utilized as
different strategies are attempted. As
performance became more successful,
variability decreases and at expert level
variability increased again, increasing
flexibility of the skill in a variety of
environmental challenges. Nakayama, et al.
(41) found that trained distance runners
showed decreased variability in stride
interval than non-runners during treadmill
running at or close to their preferred speeds.
Recently Cortes, et al. (42) noticed that also
exercise induced fatigue lead to a decrease
in variability of the ground reaction forces
and knee movements and loss of
coordination during a side-step cutting task
as typically seen in soccer.
The above study findings can be interpreted
in the following way, when the
sensorymotor system adopts a functionally
4
preferred state of coordination; the capacity
of the system to produce consistent and
stable patterns of coordination is ideal (24)
(25). Also a flexible and adaptable
sensorymotor system can adapt into optimal
states of coordination when exposed to
environmental and task demands (26).
Movement Variability and Injury
Recently research has shown that there are
a number of reasons why movement
variability is important in relationship to
running injuries, (43) (44) (45) (46), ACL
injuries (47) (48), elderly (49) (50) (51),
patellofemoral pain (43) (44) (52) and back
pain (53) (54) (55) (56) (57)
Running studies on the hip-knee Q-angle
relationship and injury risk as well as data
on running mechanics showed that
variability in coordination during the period
between initial foot contact and the neutral
position of the stance phase is an important
feature of normal, healthy running (43)
(44). Holt, et al. (52) reported similar
findings for walking, making them suggest
that this variability can have important
implications for injury prevention and
performance (43). It is speculated that
constantly varying the point of force
application during movement may prevent
overloading the same anatomical surfaces.
Also, variability in coordination could
provide the flexibility necessary to adapt to
environmental perturbations as seen in
running on uneven terrain.
In their second study, Hamill et al. (43)
examined the influence of patellofemoral
pain and the coordination of lower
extremity body segments during treadmill
running between those with vs. those
without patellofemoral pain. Heiderscheit
(58) similarly found that reduction of
patellofemoral pain coincided with an
increase in variability of the measured body
segments. A follow-up study by
Heiderscheit et al. (46) examined the
influence of patellofemoral pain on joint
coordination and stride characteristics. The
results demonstrated that stride length was
significantly greater in the injured
population. This coexisted with an
increased limb variability of the noninjured
limb and a decrease in the variability of the
injured limb.
Pollard doctoral dissertation (47) examined
variability in lower-extremity coupling in
males and females performing an
unanticipated cutting maneuver. Results
showed that women have significantly less
variability in mean thigh-leg joint coupling
during the stance phase than males. Based
on this study, Pollar (47) suggested that the
reduced variability places females under a
greater risk for knee injury. Moraiti, et al.
(48) also found that those with a deficient
ACL show decreased stride-to-stride
movement variability. Based on the above
studies it appears that for optimal
performance to occur, levels of stability and
variability must be balanced (59). It is
suggested that this relationship may be
specific per task (23) (60) (61).
Those with back pain show increased sway
in standing and sitting as compared to those
with no back pain (53) (54) (55) but hold
their trunks very stiffly; the healthy subjects
compensate the tendency to sway by
coordinated adjustments of their trunk
posture, i.e. an increased variability in this
particular part of the overall motor pattern
(54) (56).
The author suggests that injury
management can benefit from a movement
variability approach as seen in studies that
examined the relationship between pain and
movement analysis (43) (44) (52). For
5
example, examining variability in
coordination of lower extremity body
segments can monitor the effectiveness of
rehabilitation protocols.
In sum, human movement in healthy
populations are associated with an optimal
amount of movement variability. Optimal
movement variability allows performance
success and optimal health. Movement in
unhealthy populations are associated with a
less-than-optimal amount of movement
variability. These limitations may hamper
their safe return to optimal health and
performance. Performance, movement and
rehabilitation experts need to understand
what movement variability is and how they
can manipulate it so optimal movement
variability can be obtained with their
populations (62) (63) (64) (65) (66) (67)
(68) (69) (70).
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