Biomechanics and Medicine in Swimming XI

BiomechanicsandmedicineinswimmingXi
and the end of the arm stroke phases in front crawl (entry+catch, pull,
push, recovery), Chollet et al. (2000) established an index of coordination
(IdC) that quantifies the time lag between the propulsion of one
arm and that of the second arm. The IdC has been adapted for the four
strokes (backstroke, Chollet et al., 2008; butterfly, Chollet et al., 2006;
breaststroke, Chollet et al., 2004; for a review, Chollet & Seifert, 2010,
Seifert & Chollet, 2008) in order to assess the time gaps quantifying the
upper limb coordination in the alternating strokes and the upper-lower
limb coordination in the simultaneous strokes. Therefore, when IdC =
0%, the mode is opposition; when IdC < 0%, the mode is catch-up; and
when IdC > 0%, the mode is superposition. From a functional point of
view, it is nevertheless reasonable to consider the opposition mode as
-1% < IdC < 1%. It should also be noted that these indicators remain
indices of coordination and not propulsion. Coordination can be studied
from an ‘egocentric’ point of view (degrees of freedom, i.e. limb movement
possibilities like flexion and extension, pronation and supination,
rotation, etc.) rather than from an ‘allocentric’ point of view (propulsion
phases and concepts). Seifert et al. (2010a) therefore recently assessed
upper-lower coordination in breaststroke from the angle and angular
velocity of the elbow and knee to determine their coupling by the calculation
of the continuous relative phase.
Two swimmers can achieve the same performance (swimming
speed) using different modes of inter-limb coordination. Thus, a second
question arises: Is there a relationship between coordination and
performance? In other words, is there an ideal inter-limb coordination
mode? Should the coach advise the swimmer to favour superposition
coordination rather than opposition? Is the catch-up or glide mode a
technical mistake? Should the beginner imitate the expert swimmer?
Or is it reasonable to allow a temporary ‘non-expert’ coordination mode
at the beginning of the learning and training process? The aim of this
paper is to show that coordination emerges principally from interacting
constraints (Newell, 1986): environmental (aquatic resistances and
speed as resistance equal to speed squared), task (imposed by the operator,
e.g. swimming at maximal intensity, swimming in fatigue condition)
and organismic (corresponding to the swimmer’s characteristics,
i.e. anthropometry, morphology, strength, etc.). From this perspective,
the swimmer’s inter-limb coordination is a consequence of interacting
constraints and not a cause (for a review, see Davids et al., 2008). Thus,
coaches should (i) take the organismic constraints into account, (ii) find
means to minimize the environmental constraints, and (iii) manipulate
the task constraints to destabilize inadequate coordination in order to
bring about a coordination mode not expected from the beginner’s initial
behaviour. Direct manipulation of coordination to improve performance
requires great care, however, and the swimmer should initially work
at adopting the imposed behaviour without trying to improve performance.
For example, if superposition coordination is the target coordination,
the swimmer may increase his stroke frequency, thereby slipping
through the water without achieving the expected performance. When
coaches directly manipulate coordination, they therefore need to keep in
mind the importance of maintaining the same performance level.
The following sections present the similar behaviours and main differences
between expert and non-expert front crawl swimmers regarding
(i) the effects of swim speed, active drag and energy cost; (ii) the
relationships between coordination, propulsion and efficiency; (iii) the
relationships between coordination and performance, bearing in mind
that coordination may be either flexible or stable; and (iv) the effect of
breathing, which suggests that swimmers organise their limb coupling
not only to propel but also to breathe and float.
coordInAtIon, sWIM sPeed, ActIVe drAG And enerGY
cost
According to Newton’s second law ( ∑ F = m. a , where F is the force, m
the mass and a the acceleration), forward body displacement is related
to the differences between the propulsive forces generated by the swimmer
and the aquatic resistive forces (i.e. the environmental constraints).
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In fact, forward body displacement seems to be a more complex process
and the swimmer may cross several solutions, probably the production of
propulsive forces, the minimization of active drag, the maximization of
propulsive efficiency (i.e. minimization of kinetic energy) and the monitoring
of inter-limb coordination.
Thus, when active drag and speed (active drag changes with speed
squared) increase, inter-limb coordination is affected, particularly by a
decrease in the time lag between two propulsions, which means that
the relative duration of the glide and catch phases decreases. In front
crawl, Chollet et al. (2000) and Seifert et al. (2004, 2007b) showed that
speed increases lead to similar motor behaviour in expert male, expert
female, and non-expert male swimmers: they increase the IdC and simultaneously
increase stroke rate and decrease stroke length. Seifert et
al. (2010b) used an arms-only protocol both on the Measuring Active
Drag (MAD) system to assess active drag during an incremental test
and while swimming in free condition to assess inter-arm coordination
in front crawl. They showed a linear regression between active drag and
IdC (0.64 < R² < 0.98), confirming that swimmers have to modify their
motor organization when the task (speed) and environmental (drag)
constraints increase.
Similar results were found when energy cost increased: reaching
higher speed leads to higher energy expenditure and increases IdC and
stroke rate (Morais et al., 2008; Seifert et al., 2009).
coordInAtIon, ProPulsIon And eFFIcIencY
Only expert swimmers attain high speeds, as they are able to generate
high power output and reach high IdC. Indeed, when expert swimmers
increase their speed and/or their stroke rate above a critical value (respectively
~1.8 m.s -1 and 50 stroke.min -1 ), only the superposition mode
is observed (Potdevin et al., 2006; Seifert et al., 2007b), which may be
attributed to the dominance of wave drag. When moving at high speed
in whole stroke (> 1.5-1.7 m.s -1 ), wave drag becomes even greater, accounting
for up to 50-60% of total drag (Toussaint & Truijens, 2005;
Vennell et al., 2006). Using a process similar to the calculation of “hull
speed” for a ship, the authors mentioned above found that the hull speed
for a swimmer with an arbitrary height of 2 m was 1.77 m.s -1 (Toussaint
& Truijens, 2005). This finding coincides with the large increase in active
drag found above this critical speed (> 1.7-1.8 m.s -1 ), as determined
by the wave drag, the environmental constraints eliciting a superposition
coordination of the arms. Indeed, it was recently shown that an
increase in speed leads to simultaneous changes in drag force, power
output and inter-arm coordination. While swimming only with arms
in the free swimming condition, expert front crawl swimmers switch
the inter-arm coordination from catch-up mode (IdC < 0%) to superposition
mode (IdC > 0%) above a speed of 1.5-1.6 m.s -1 at maximal
intensity (Seifert et al., 2010c). Using arms-only on the MAD system,
the same swimmers exhibited a drag force of 100-110 N at maximal
intensity, developing a mechanical power output of ~200 W (Seifert et
al., 2010c). Conversely, less-expert swimmers also swimming at maximal
speed exhibited a drag force < 100 N, power output < 180 W and interarm
coordination in catch-up mode (IdC < -6%), which did not enable
them to reach the same speeds as the expert swimmers. On the other
hand, a high IdC does not guarantee high speed, as the swimmer can
slip through the water and/or spend a long time in the propulsive phase
because of slowed hand speed, meaning low propulsive efficiency. Notably,
Seifert et al. (2010b) showed that IdC increases with active drag
in experts, but that at maximal intensity (swimming 25m all out) IdC
is not correlated with propulsive efficiency for this sample of swimmers.
Moreover, when speed increased, expert swimmers increased IdC while
their hip intra-cyclic speed variation remained stable with a coefficient
of variation close to 0.15 (Schnitzler et al., 2008; Seifert et al., 2010c).
Conversely, non-expert swimmers did not significantly change their
arm coordination (which remained in catch-up mode) while their hip
intra-cyclic speed variation increased (from 0.16 to 0.21). These results
suggest that, unlike non-experts, expert swimmers make effective motor