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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