Download 1. Introduction

Fatigue & perception of the effort during an orienteering
race
Blanchard1, Mickael, Grison1, Benoit, Ravier2, Philippe, and Buttelli1, Olivier.
. Laboratoire Activité Motrice et Conception ergOnomique (AMCO), Université d’Orléans.
2.
Laboratoire Electronique Signal Image (LESI), Université d’Orléans.
1
We tried to analyse the effort during an orienteering race by working on the objective
and subjective perception of the effort made by the runner before during and after a race.
The physiological approach was studied by heart rate activity. This activity was
recorded by the electrocardiograph activity (ECG). The heart rate activity (HRV) was
analysed thanks too frequencies parametric techniques (Pburg’s method), and timefrequency linked (method with Morlet wavelet). The psychological approach was studied by
interviews focused on the progress of the race. These interviews were compared to data of
ECG’s records. All this datas was recall with observables (climb, type of ground,…) to
understand the modifications of heart’s data. The ECG was analysed in two frequencies
bands (Low frequencies (LF), 0.04 to 0.15 Hz ; High frequencies (HF), 0.15 to 0.3 Hz). For all
them, the quantity of energy (power) was evaluated.
We notice many changes after the effort in comparison to the variables of rest before
v.s. after the effort: increase of LF band’s power and decrease of power HF band’s power. In
race situation, we can also observe a psychological influence on the energy of HF band and
a physiological difference on the energy of LF band. The HF would be a reliable marker of
the cognitive effort put in the task during the orienteering race.
These results could help us manage the effort in a finer way working with the athletes
in order to put in place a system of help which will improve the diagnosis of the orienteer.
Keywords: orienteering, perceived exertion, HRV, interviews, psychology, physiology.
1. Introduction
The aim of this study was to
apprehend biological and psychological
stress in orienteering race, working on the
objective assessment of the effort of the
runner in his physiological dimension and
his subjective perception before, during
and after a race.
A transversal approach of tiredness
has been chosen. We have used in our
study, methods which come from cognitive
anthropology and physiology in order to
analyse the orienteering course.
The sportsman follows on his own
an orienteering circuit, he is only helped by
his usual tools (map, compass) he controls
on his own. The runner’s performance is
conditioned by many stresses due to the
fact he evolves in an open and
complicated milieu. That’s why the
physiological data don’t enable to explain
the sport winning. We have to take into
consideration the conditions in which the
performance is made. We also have to
take into account the subjective factors
(feelings, motivation) within the frame an
approach of the runner’s cognition. It is
then important to put the runner back into
the context in order to study his actions in
his complicated environment.
To
catch
this
dynamical
environment, as Plaza (1989) says, the
study of individual, in situation, implies
interdisciplinarity on theorical point of view,
and in the same time using different tools
on practical point of view because each
1
specialist only has a patchy view of the
problem, this view is related with the
object of his study. We have tried to cast
new light on our problem from the data
resucting from the analysis of the
variability of the heart rate variability
(HRV) and from the subjective data after
the interviews.
Authors such as Karppinen (1994)
or Peck (1990) have shown that there was
no link or linear evolution by comparing
the efforts made during an outdoor race to
laboratory studies. Orienteering race is a
special activity we have to study in natural
milieu, the physiological answer in
orienteering race being singular. Our
experiments will be made in real
conditions, on the usual ground.
However, the practical situations
cannot be reduced to situations rebuilt in
laboratories, more “artificial” situations
than original practical situations, it’s
difficult to apply rigorous experimental
control. The profusion of variables implied
in practical situations as well as the
numerous interactions between these
variables make delicate the validity of the
explanation and make dangerous its
degree of generalization. (Grison, B. &
Riff, J., 2002)
1.1. Cognitive anthropology –
situated actions
In this study, methods come from
the situated actions trend, which
considerate that action must be interpreted
compare with his context, context “which
recovers group of values taken by the
parameters which describe the physic
world state at a moment” (Salembier,
1996). Action and situation define each
other, the context is at once the product of
the activity and of the individual, and the
action’s frame, that Lave (1988) calls
« mutual and successive determination »
of the actors and his environment.
Theureau (2004), illustrates anchoring of
the action in unique context “the cognition
is not situated in this head, but in between,
between the actors and the situation,
which the other actors take part” and so
advocate the study of actors in real
situation, significant for them. Then it
matters to replace the actor in the context
to study him. (Suchman, 1987). This
theory proposes frame of reference more
adapted to the activity than the one
proposed by the cognitivists. Then we will
use non directive interviews, to go into the
own activity of the actors in real situation
in greater depth. The race situations
include the environment and the actor
associated to his goals and his cultures.
That is why the interviews realized have
been centred on the real actions and
based on the marks of the action which is
available: time realized to run each
itinerary, the map and the route achieved.
1.2. Physiology – Heart rate
variability
The electrocardiogram (ECG) is
the line obtained by the recording of the
potentials of actions generated by heart.
The ECG shows different complexes, in
particular QRS complex, linked to the
ventricular activity. The duration in
milliseconds (ms) separating two peaks R
produces heart rate (HR). The study of the
heart rate variability (HRV) quantifies the
variations of R-R intervals in frequency
domain. The variations of this heart rate is
control by autonomic nervous system.
The autonomic nervous system is
constituted
by
two
parts:
i)
parasympathetic nervous system, ii)
sympathetic
nervous
system.
The
regulation of heart rate is the consequence
of skilful linkage of the both systems:
sympathovagal
balance.
The
parasympathetic nervous system is above
all predominating in “rest” situations (in
2
opposition to physicals activities): it is
associated in particular to rest and
digestion. His principal function consists in
minimizing energy consumption while it
allows the achievement of the vital
functions. On the other hand, sympathetic
nervous system under stress conditions,
like in emergency situations (e.g. escaping
or struggling) or during physical activity.
His influence is characterized by the
increase of cardiac and respiratory
frequencies.
This balance can be observed
through cardiac activity. Indeed, when an
analysis of the heart rate variability (HRV)
is realized, different ranges of frequencies
are determined in relation to the activities
of these two systems. The quantification of
this activity can be realized in time and
frequency domains. (Task Force of
European Society of cardiology, 1996)
Different methods allow to change
from a time signal to a frequential signal.
We can distinguish two approaches: this
parametric and this non-parametrics. The
parametrics approaches allow to simplify
the studies signal in order to reveal
privileged frequencies bands. Their
disadvantage is due to the necessity of
choosing the parameters, choice can be
tricky in some cases. Furthermore, when
it’s necessary to follow the evolution of a
signal, it’s preferable to use an analysing
method which changes with the time
(Samar et al., 1999), signal which
characteristic is non-stationary.
In
frequency
domain,
two
frequency bands are pertinent compared
with autonomous nervous system’s
activity. (Akselrod 1981):
o A high frequency (HF) focused
on the breathing rhythm and
controlled by the parasympathetic
nervous system, ≥ 0,15 Hz ;
o A low frequency (LF) controlled
by the sympathetic nervous system
and parasympathetic, probably shows
the de sensibility of the baroreflex,
0,04 ≤ LF < 0,15 Hz ; The LF band
being the image of the 2 systems, it is
interesting to study the LF/HF ratio to
evaluate the importance of the
sympathic nervous system’s action ;
These frequencies bands are
sensitive to the situation in which the
subject is: (Jouanin et al., 2004)
o supine v.s. upright position;
o rest v.s. activity ;
o high cognitive activity v.s. low
cognitive activity ;
o and also the conatives stress
he’s exposed.
The changing of the distribution of
energy in the different bands as presented
on the top enables to follow the
sympathovagal
balance.
LetourmyLecarpentier et Larue (2000) have shown
a significant change between the energy
included in the HF bands and the cognitive
activity.
We will study the runners’ ECG by
linking those analyses to the observations
made and to the data from the non
directives interviews based on the singular
action study. These methods will be used
in order to take into account the whole
specificity of the first aim: Apprehending
the effort in orienteering, in working on
perception
exertion
objective
and
subjective individual effort, before, during,
and after an orienteering race.
The goal of this study is to find a
physiological marker which reacts to the
effort put into the tasks during an
orienteering race.
2. Method
3
This work has been done with high
level athletes from the French Pole in St
Etienne. There were 12 subjects
consenting all from the French national
team.
2.1. General procedures
The collection of the data was done
in two sections. At the beginning, the
different subjects should have been there
on the same day for the data to be
collected in the same condition.
Total n=12
average s.d.
âge
21,3
3,5
years of pratical
8,8
4,4
training / week
4,5
0,9
2.2. Protocol
The runner had to do an
orienteering race, during a competition
(n=5) or during a training (n=7). The
runners were equipped by with holter
which recorded their ECG and did a
orthostatic test (stand-test, Hedelin et al.,
2001) before and after the race.
This test consists in measuring the
ECG for 5 minutes in supine position
resting time and followed by 6 minutes in
upright position. The breathing frequency
was free. Moreover the ECG was recorded
during the full time of the race. After the
race a non directive interview, focused on
his race and his perceptions was done in
order to get information to link with the
recording of the ECG.
2.3. Data collection
The recording of the ECG was
done on 2 channels with a 500 Hz
frequency during the stand-tests before
and after the race, and also during the
race.
Figure 1 : execution of data collection.
To synchronize our data from the
ECG and the study we have used 2
separate “sections”:
o sections
referring
to
the
segmentation of the race, control by
control;
o smaller sections referring to the
cutting out of the race, observable by
observable (at each change of
altitude, of slope…); The time being
only known at every control, to situate
temporal boundary, we have used an
average of speed on each section.
(figure 2)
Figure 2 : example of cutting out in section
and the average of the speed.
The non directives interviews done
for the study are linked to an effective
action: the execution of his race. The
runner tries to live his race again and to
tell how it went on. He begins by the firsts
events he considers as important in the
performing of his race. The first question
was the one at the beginning. All the other
interventions were about the centring on
the subject or clarification on the story. I
tried to put the athlete at ease and I
advised him to have a chronological
development. The evaluation of the
4
runner’s feeling of speed was helped
thanks to a tool: he could tell me thanks to
3 colours (green, orange and red) his
speed. This tool helped him to start the
interview. (figure 3)
Figure 3 : example of coding of the speed
felt by the runner.
The data collection helped us to
get three types of data:
o from the moving activity (split
times,
climb,
type
of
the
ground…)(=activity marks);
o from the recording (ECG);
o from
interviews
collected
afterwards.
thanks to a test on rank to Wilcoxon
(SigmaStats v.3 Systat®). Significant
threshold were fixed at p ≤ 0,05.
2.6. Synchronization of the
spectrogram to observables
We then tried to understand the
“rough” physiological data: The timefrequency representations (spectrograms)
thanks to data from interviews and
observable too.
To do this work, we chronologically
took the subject’s speech, trying to
correlate to the spectrogram without any
theoretical presupposition. Only the data
from 5 subjects could be analysed. These
results will be explained in the next part.
3. Results
3.1. Results from stand-tests
2.4. Treatment
The heart frequency’s variability
was evaluated from the ECG recording.
The ECG data were analysed
thanks to Matlab® 6.5 software.
The standard deviation of the R-R
interval (SDNN) was calculated.
The different frequencies bands of
the HRV were calculated thanks to
parametric analyse (Pburg [P order fixe at
9]) and time-frequency by continous Morlet
wavelet (Karlsson,S et al., 1999). The
spectrogram come from this analysis timefrequency. The energy of frequency bands
(LF, HF) found from the techniques
mentioned above was normalized to total
energy of the two bands and allow us to
define LFnu and HFnu according to the
formula (Cottin, 2003):
LFnu = LF/(LF+HF)x100
HFnu = HF/(LF+HF)x100
3.1.1. Before effort
For
LF/HF
ratio,
significant
increase between the supine position and
upright position (p= 0,01).
The normalised values of LF and
HF show an increase of the LFnu and at
the same time a decrease of the HFnu.
3.1.2. After effort
We can observe an increase of
LFnu and at the same time a decrease of
the HFnu (p=0,039).
3.1.3. Supine position
Concerning SDNN, a significant
increase is observed (p= 0,008). (figure 4)
2.5. Statistics procedure
Statistics on the stand-tests supine
position v.s. upright position, and the
comparisons before v.s. after were done
5
Figure 4 : evolution of the variability of
SDNN (short-term variability of HRV)
between before (
) and after (
) effort
in both situations (supine and upright). p< 0,05
(**) ; p<0 ,055 (*)
3.1.4. Upright position
The HF band presents a significant
growth (p= 0,005). The LF/HF ratio
increases
significantly
(p=
0,033).
Concerning the SDNN a significant growth
is observed (p= 0,03).
3.2. Results in race conditions
This example (figure 5) highlights
the relation between a spectrogram from a
time-frequency
analysis
and
the
corresponding
interview.
This
synchronization reveals the relations
between the spectrogram and the
corresponding interview.
The psychological factors such as
orienteering mistakes, reading the map in
complex places…increase the energy
power of the HF band. On the other hand,
physiological factors such as the speed
during the race, the use of the paths…
increase the energy power of the LF band.
This relation has also been noticed for the
5 other subjects.
6
4. Discussions
We have to notice that the
standard deviation is very high for all the
data. We can explain that by different
runners’ race in this study. Indeed, the
orienteers have ran on different maps,
different ground: climb, time, vegetation,…
These differences had an influence on the
individual answer. (Karppinen, 1994, Peck,
1990).
4.1. The stand tests
In our study, the LF/HF ratio
increases between the supine position v.s.
upright at rest. That shows the LF band
take a more important part of energy than
HF bands. This data is in line the Task
force (1996). Our data confirms the data
found in laboratory and on the field by
other studies. This let’s us think that the
methods used in this study and the data
we have found are reliable.
The growth of the standard
deviation of the RR (SDNN) after race
gaps shows that the tired subject has a
bigger variation of the time of this interval,
like Jouanin observes (2004) after
prolonged tiredness due to 7 days of
effort. (figure 4)
After race, the ratio LF/HF
increase, although the energy of HF band
increases. We can explain that by the
increase is due to higher growth of energy
of LF band. This enables us to conclude
in our situation that the sympathetic
nervous system has more importance at
response to endurance effort.
The results of normalized values to
LF (LFnu) and HF (HFnu) corroborate the
evolution of the ratio LF/HF. The increase
of this ratio shows the preponderance of
the sympathetic nervous system activity
after the effort and the preponderance of
a sympathetic tiredness induce by the race
This goes against other studies which
highlighted a growth of the activation of
the parasympathic nervous system after
the effort (Jouanin et al., 2004). This
difference can be explained, on the one
hand, by the race duration, in your study,
was most short (average: one hour thirty
minutes) than in the study of Jouanin et al.
(2004) (a intensive period training of 7
days). On the other hand, this different can
be explained by the time when the standtest has been done after the effort. In case
of recovery, the decrease of the heart
frequency is first due to the activity of the
sympathic nervous system (increase of
activation) and then of the parasympathic
nervous system (increase of activation)
(Pierpont et al., 2000). In us study, the
stand-tests had realize just after the stop
of exercise, although their heart frequency
was still high. The results of the ratio
LF/HF would probably be different if the
stand-tests took place later, after a more
long time of recovery like in Jouanin’s and
al. study (2004).
4.2. Relation between subjective
perception and biological marks
The relation between spectrogram,
observables, and interviews (qualitative
analysis) allowed us to formulate the
hypothesis that LF band would link to the
regulation of physical effort (e.g. speed),
and the HF band could be linked with
cognitive stress and restricting situations
(e.g. mistakes). However, the influence of
these psychological factors could be
indirect. Indeed, the map reading requires
the map stabilization, and in extension, the
arms, which infers speed running
decrease. Consequently, it’s this slowing
down which could start to the increase of
the band HF. Nevertheless, factors like
orienteering mistakes, which don’t affect
the running speed, lead to the same
modifications on the LF band. It allows us
to think that this band responds directly to
psychological factors. It means HF band
7
could be a marker to cognitive effort, even
when there is concomitance with high
physical effort, as it was proved in
experimental situations in laboratory.
(Letourmy - Lecarpentier et Larue, 2000)
However, for this last study, the
measurements were taken during a limited
physical effort and well delimit (Fitts
“cognitive” tasks with 5 min recording).
This results could permit us a fine
precision of psychological stress in relation
to the races’ situations and could be
realize the quantification to this stress.
This tool could be building a help system
to management of effort in race.
5. Conclusion
The linked between biological’s
indicators (e.g. heart rate variability) and
race’s stress and perceived of race’s
stress, could be made a usefully tools for
the runner in order to obtain the most
objective feedback. The objective will be to
equip the runner with useful markers to
manage his effort, a mental one as well as
a physical one. In consequently, this
method could be integrated, in the same
way as the physical preparation, in daily
planning of training.
To continue this study, it seems
necessary to improve the synchronization
of our data. In this goal, we must modify
some protocol’s points to take in
consideration the comments expressed
above:
o All the subjects have to run on
the same circuit to reduce the number
of variables in order to standardize
the situation for all subjects ; all the
runners must have the same circuit,
for example they could alternate a
fixed circuit (a route followed: all the
subjects have the same real route,
with the same climb, the same
vegetation, the same problem of map
reading,…) and the classical circuit
(like this year, when the runner was
free of his route).
o The bad precision of our data
positioning so the approximate
synchronization of the biological and
the psychological markers : the
cutting out of sections and the
average of the speed to synchronize
the different of observables lead to a
gap too important between the real
positioning of runners and their
positioning estimated when the
controls to controls are distant, and/or
with an intermittent climb; To solve
this problem, the equipment of GPS
for each runner becomes necessary;
It would allow to detail the sections
with a perceptiveness of grain which
makes possible the synchronization of
any observable of course to the ECG
without deviation (figure 2, page 4);
These improvements should allow
a better apprehension of the real
orienteers’ activity during the race.
Bibliography:
Akselrod, S., al. (1981). Power spectrum
analysis of heart rate fluctuation: a
quantitative
probe
of
beat-to-beat
cardiovascular control. Science ,213, 220222.
Cottin, F., Durbin, F., Papelier, Y. (2003).
Heart
rate
variability
during
cycloergometric exercise or judo wrestling
eliciting the same heart rate. European
Journal of Applied Physiology, 90, 352367.
Grison, B., Riff, J. (2002). Validité
écologique
et
situations
d'étude
privilégiées
:
de
la
psychologie
expérimentale à l'anthropologie cognitive
située. In Actes 4èmes Journées d'Etudes
de
l'Association
ACT'ING,
'Objets
théoriques, objets de conception, objets
d'analyse
et
situations
d'étude
8
privilégiées', 6-7 juin, Domaine de Chalès,
Sologne.
Hedelin, R., Bjerle, P., Henriksson-Larsen,
K. (2001). Heart rate variability in athletes:
relationship with central and peripheral
performance. Med. Sci. Sports Exerc., 33,
1394-1398.
Jouanin, J.C., Dussault, C., Pérès, M.,
Satabin, P., Piécard, C., Guézennec, Y.
(2004). Analysis of heart ratevariability
after a ranger training course. Military
Medicine, 169, 583-587.
Karppinen, T., Laukkanen, R. (1994).
Heart rate analysis in orienteering training
and competition before and during WOC
1993. Scientific Journal of Orienteering,
10, 63-77.
Karlsson S, Yu J, Akay M (1999).
Enhancement of spectral analysis of
myoelectric
signals
during
static
contractions using wavelet methods. IEEE
Trans Biomed Engin 46: 670-684
Lave, J. (1988). Cognition in practice:
Mind, mathematics and culture in every
day life. New York: Cambridge University
Press.
Letourmy-Lecarpentier, C., Larue, J.
(2000). La variabilité de la fréquence
cardiaque comme indice physiologique de
l’effort investi dans des tâches cognitives.
Congrès International de la SFPS - Paris
INSEP.
Salembier, P. (1996). Cognition(s) : située,
distribuée, socialement paragée, etc.
Bulletin du LCPE, 1, Paris: École normale
supérieure.
Samar, V., Bopardikar, A., Rao, R.,
Swartz, K. (1999). Wavelet analysis of
neuroelectric waveforms: A conceptual
tutorial. Brain and Language, 66, 7-60,
Suchman, L. (1987). Plans and situated
actions.
Cambridge
:
Cambridge
University Press.
Task force of the European Society of
Cardiology and the North American
Society of Pacing and Electrophysiology
(1996). Heart rate variability. Standards of
measurement, Physiological Interpretation,
and clinical use. Circulation, 93, 1043-65.
Theureau, J. (2004). Le cours d'action :
méthode élémentaire. Toulouse : Octarès.
Le mémoire de Master 2 duquel est tiré
cet article :
http://stapsmicka.free.fr/DEA_BR.pdf
Mickaël Blanchard
La Noue
37360 Sonzay France
[email protected]
Peck, G. (1990). Measuring heartrate as
an indicator of physiological stress in
relation to orienteering performance.
Scientific Journal of Orienteering, 6, 26-42.
Pierpont, G.L., Stolpman, D.R., Gornick,
C.C. (2000). Heart rate recovery postexercice as an index of parasympathetic
activity. Journal of the Autonomic Nervous
System, 80, 169-174.
Plaza, M. (1989). La psychologie clinique :
les enjeux d’une discipline. In Revault
d’Allonnes, C., La démarche clinique en
sciences humaines. Paris : Dunod, 3-16.
9