Biomechanics and Medicine in Swimming XI

Muscle Fatigue in Swimming
rouard, A.h.
Laboratoire de Physiologie de l’Exercice, Université de Savoie, France
Fatigue is a complex process which could be related to different alterations
either of the central nervous system and/or of the muscles.
Few studies have focused on the biomechanical evaluation of fatigue
in swimming. EMG results indicated either an increase of integrated
EMG (IEMG) for muscles with sub-maximal activation or a decrease
of IEMG for muscles strongly involved. Moreover, the frequency contents
shift toward lower frequencies either for Maximal Voluntary Contraction
(MVC) realised before and after an exhaustive test or during a
maximal swimming test. Changes in muscular activation were associated
with a decrease of force production (dry land strength or tethered or
semi-tethered or swimming hand forces) and to changes in the path of
the hand. Fatigue appears to be related to the task, the subject and the
muscle.
Key words: front crawl, fatigue, electromyography, forces, kinematics.
IntroductIon
The swimmers performance is determined by the ability to generate
propulsive forces while reducing the resistance to forward motion. Propulsive
forces are mainly generated by 3D limb movements in response
to unstable loads created by the water. As in all human activities, fatigue
could be defined as an acute impairment of performance. In regard to
the movement generation process, fatigue could be related to central
and/or peripheral alterations. The central component of fatigue could be
due to the decrease of the CNS activation (nervous order and/ or motor
neuron activation). The peripheral fatigue is related to an alteration
of the neuromuscular junction and/or the deficit of substrates, blood
flow, and/or dysfunction of the sarcomer. Consequently, fatigue is a very
complex phenomenon, which could be evaluated through different approaches
(physiology, Electromyography (EMG) and Mechanics).
Because of the complexity of the movement in an aquatic environment,
few biomechanical studies have focused on fatigue in swimming.
EMG has largely been used in the evaluation of fatigue during sustained
isometric contractions. Many authors have observed a shift to
lower frequencies of the EMG signal spectrum. In the 90’s, a novel approach
(time-frequency treatment) was proposed for calculating spectral
parameters from the surface myo-electric signal during cyclic dynamic
contractions for which changes in muscle length, force and electrode
position contributed to the non-stationary status of the signal (Knaflitz
and Bonato, 1999). Recently this approach was applied to swimming
movement (Caty et al, 2007).
The present review concerns the effect of fatigue on muscular activation
and the associated changes in forces and hand trajectories
Methods
Most of the studies on fatigue in swimming have been conducted on
male international swimmers. Different maximal tests were performed
by the subjects depending on the authors (i.e. maximal 400m swim in a
flume for Monteil et al, 1996, or maximal 4*50m for Caty et al, 2007).
During the test, EMG was synchronised with video acquisition. For
EMG, the authors used either surface electrodes (Wakayoshi et al, 1994,
Rouard et al, 1997, Caty et al, 2007) or fine wire electrodes (Monteil et al,
1996). Shoulder and upper limb muscles were those most investigated.
All the authors applied the same guidelines for the location of the electrodes
(belly of the muscle) and the skin preparation (Clarys and Cabri,
1993). Signals were stored on a memory card or on the soundtrack of the
video camera. For the amplitude treatment, the raw EMG signals were
rectified, smoothed and then integrated (IEMG). For each subject, and
each muscle, the IEMG were normalised according to the maximal dy-
chaPter1.invitedLectures
namic value observed during the testing procedures. For the frequency
treatment, Aujouannet et al (2006) applied a Fourier transformation to
evaluate the frequency contents of static Maximal Voluntary Contractions
(MVC) performed just before and after the exhaustive swimming
test (4*50m). For the swimming signals, Caty et al (2007) extracted, with
a statistical detector, the activation interval corresponding to each stroke
and each muscle. For each detected muscle burst, the Choi-Williams
transformation was then computed. These particular transformations
had already proven effective in the analysis of strongly non-stationary
EMG signals recorded during dynamic exercise (Knaflitz and Bonato,
1999). The instantaneous mean frequency of the signal burst (MNF, Hz)
was calculated for each stroke cycle.
For the kinematic evaluation of fatigue, at least 2 underwater cameras
were used to analyse the 3D movements of the upper limbs. The
video was digitised frame by frame to get the hand trajectories and/or
the hand velocity and/or different angles (sweep back and attack hand
angles, limbs angles).
During the MVC, the forces were recorded using a strain gauge, while
during swimming the authors used either direct force measurements
such as a tethered or semi- tethered apparatus (Aujouannet et al, 2006,
Rouard et al, 2006) or an indirect approach calculating the lift, drag
and resultant hand forces according to Schleihauf ’s method (Monteil
et al, 1996)
results
Results indicated a decrease of IEMG for the most activated muscles
(M. Deltoideus or M. Flexor carpi) (Wakayoshi et al, 1994; Caty et al,
2007) (Figure 1) or an increase of IEMG for muscles with sub-maximal
contractions depending on the phase of the stroke (M internal or external
rotators) (Monteil, 1996) (Figure 2).
Figure 1: Mean (SD) of the normalised IEMG of the muscles Flexor
(FCU) and Extensor (ECU) carpi ulnaris for the 1 st and the 4 th of the
maximal 4* 50m test (adapted from Caty et al, 2007)
Figure 2: Normalised IEMG of the shoulder muscles at the beginning
(fresh) and end (fatigue) of a maximal 400m test swam in a flume
(adapted from Monteil et al, 1996).
A shift of spectral parameters of the EMG’s of the M. biceps and triceps
brachii toward lower frequency was observed during maximal voluntary
contractions (MVC) realised before and after a maximal 4*50m swimming
test (Aujouannet et al, 2006). During the 4*50maximal test a de-
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