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1. BRG.LifeMOD$^{TM}$ modeling and simulation of swimmers impulse during a grab start

Author

Agnesina, Guillaume, Taiar, Redha, Houel, Nicolas, Guelton, Kevin, Hellard, Philippe, and Toshev, Yuli

Subjects
Physics - Medical Physics
Abstract

The main aim of the study is to propose an approach for 3D modeling and simulation of swimmers impulse during a grab start. Four national level swimmers were investigated. For every swimmer, 3D model was generated in BRG.LifeMOD TM on the base of individual morphologic parameters and kinematic data obtained by high speed video camera and passive markers attached at the level of each important articulation. The proposed approach allows predicting swimmer's joint moments for each important articulation during the impulse phase of the grab start and to analyze the segmental coordination for each studied swimmer in order to optimize the performance. The model was successfully validated by comparing the predicted speed and power values with experimental ground reactions data collected in situ.

Published
2019

2. Career factors related to winning Olympic medals in swimming.

Author

Tchamkerten, Aslan, Chaudron, Paul, Girard, Nicolas, Monnier, Antoine, Pyne, David B., and Hellard, Philippe

Subjects
OLYMPIC medals, INDEPENDENT variables, OLYMPIC Games, SWIMMING, WORLD championships
Abstract

To investigate associations between a swimmer's career progression and winning a medal at the Olympic Games (OG) or World Championships (WC). A total of 4631 swimming performances of 1535 top swimmers (653 women, 882 men) from 105 nationalities since1973 were extracted from FINA rankings. A panel of 12 predictor variables including nationality, gender, competition, age, number and timing of competitions, pattern of progressions and regressions in performance, and medal outcomes was established. Linear logistic regression was used to study the association between winning a medal and predictor variables. Logistic regression coefficients were obtained by training on 80% of the database, and prediction accuracy evaluated on the remaining 20%. Using the training set, a selection of 9 most relevant features for prediction of winning a medal (target variable) was obtained through exhaustive feature selection and cross-validation: nationality, competition, number of competitions, number of annual career progressions (nb_prog), maximum annual career progression (max-progr), number of annual career regressions (nb_reg), age at maximum annual progression, P6 (the level of performance six months before the World Championships or Olympic Games), and P2 (the level of performance two months before the World Championships or Olympic Games). A logistic regression model was built and retrained on the entire training set achieved an area under the ROC curve of ~90% on the test set. The odds of winning a medal increased by 1.64 (95% CI, 1.39–1.91) and 1.44 (1.22–1.72) for each unit of increase in max-progr and n-prog, respectively. Odds of winning a medal decreased by 0.60 (0.49–0.72) for a unit increase in n-reg. In contrast, the odds increased by 1.70 (1.39–2.07) and 4.35 (3.48–5.42) for improvements in the 6 and 2 months before competition (P<0.001, for all variables). The likelihood of a swimmer winning an international medal is improved by ~40–90% with progressions from season-to-season, and reducing the number of regressions in performance. The chances of success are also improved 2- to 4-fold by substantial improvements in performance in the months before competition. [ABSTRACT FROM AUTHOR]

Published
2024
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5. International Swimming League: Do Successive Events Lead to Improve Swimming Performance?

Author

Pla, Robin, Leroy, Arthur, Raineteau, Yannis, and Hellard, Philippe

Subjects
AGE distribution, RESEARCH methodology, SEX distribution, COMPARATIVE studies, SWIMMING, ATHLETIC ability, SPORTS events
Abstract

Purpose: To quantify the impact of successive competitions on swimming performance in world-class swimmers. Methods: An entire data set of all events swum during a new competition named the International Swimming League was collected. A Bayesian linear mixed model has been proposed to evaluate whether a progression could be observed during the International Swimming League's successive competitions and to quantify this effect according to event, age, and gender. Results: An overall progression of 0.0005 (0.0001 to 0.0010) m/s/d was observed. The daily mean progression (ie, faster performance) was twice as high for men as for women (0.0008 [0.00 to 0.0014] vs 0.0003 [−0.0003 to 0.0009] m·s−1). A tendency toward higher progression for middle distances (200 and 400 m) and for swimmers of a higher caliber (above 850 FINA [Fédération Internationale de Natation] points) was also observed. Swimmers between 23 and 26 years of age seemed to improve their swimming speed more in comparison with the other swimmers. Conclusions: This new league format, which involves several competitions in a row, seems to allow for an enhancement in swimming performance. Coaches and their support staff can now adapt their periodization plan in order to promote competition participation. [ABSTRACT FROM AUTHOR]

Published
2022
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6. Kinematic and dynamic analyses of the front crawl tumble turn in elite female swimmers.

Author

Puel, Frédéric, Morlier, Julien, Pyne, David, and Hellard, Philippe

Subjects
STATISTICS, THREE-dimensional imaging, TIME, WATER, SWIMMING, ATHLETIC ability, KINEMATICS
Abstract

Based on a three-dimensional (3D) underwater analysis, the objective of the present study was to identify the biomechanical variables the most associated with turn times in 10 elite female swimmers. For each participant (95.7 ± 2.6% of the 200 m freestyle world record), the best-time turn (from 3 m in to 3 m out, 2.89 ± 0.08 s) was analysed from a three-dimensional (3D) direct linear transformation kinematical reconstruction and the use of a piezoelectric force platform. Bivariate analysis showed that lateral impulse was linked to turn time (r = -0.76, p = 0.01) as well as horizontal velocities at end of the glide and swim resumption (respectively, 1.88 ± 0.2 m·s−1 and 1.48 ± 0.15 m·s−1; r = -0.67 and -0.68; p < 0.05 for both variables). One variable was considered relevant in the best Lasso (Least Absolute Shrinkage and Selection Operator) model: the lateral impulse (8.8 ± 5.1 N·s) during the placement sub-phase.The best tumble turn times were associated with higher lateral impulse during the placement and faster velocities during the underwater actions. The lateral impulse may reflect the swimmers' longitudinal rotation which was higher for the fastest swimmers. [ABSTRACT FROM AUTHOR]

Published
2023
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11. Dynamics of the Metabolic Response During a Competitive 100-m Freestyle in Elite Male Swimmers.

Author

Hellard, Philippe, Pla, Robin, Rodríguez, Ferran A., Simbana, David, and Pyne, David B.

Subjects
ATHLETIC ability, CONFIDENCE intervals, ENERGY metabolism, LACTATES, SWIMMING, AEROBIC capacity, ELITE athletes, OXYGEN consumption, MALE athletes, DESCRIPTIVE statistics
Abstract

Purpose: To compare the dynamics of maximal oxygen uptake ( V ˙ O 2 ), blood lactate ([La]b), total energy expenditure (Etot), and contributions of the aerobic (Eaer), alactic anaerobic (Ean,al), and lactic anaerobic (Ean,lac) metabolic energy pathways over 4 consecutive 25-m laps (L0–25, L25–50, etc) of a 100-m maximal freestyle swim. Methods: Elite swimmers comprising 26 juniors (age = 16 [1] y) and 23 seniors (age = 24 [5] y) performed 100 m at maximal speed and then 3 trials (25, 50, and 75 m) at the same pace as that of the 100 m. [La]b was collected, and V ˙ O 2 was measured 20 s postexercise. Results: The estimated energetic contributions for the 100-m trial are presented as mean (SD): Eaer, 51% (8%); Ean,al, 18% (2%); Ean,lac, 31% (9%). V ˙ O 2 increased from L0–25 to L25–50 (mean = 3.5 L·min−1; 90% confidence interval [CI], 3.4–3.7 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.3 L·min−1) and then stabilized in the 2nd 50 m (mean = 4.1 L·min−1; 90% CI, 3.9–4.3 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.4 L·min−1). Etot (juniors, 138 [18] kJ; seniors, 168 [26] kJ), Ean,al (juniors, 27 [3] kJ; seniors, 30 [3] kJ), and Ean,lac (juniors, 38 [12] kJ; seniors, 62 [24] kJ) were 11–58% higher in seniors. Faster swimmers (n = 26) had higher V ˙ O 2 (4.6 L · min − 1 , 90% CI 4.4–4.8 L·min−1 vs 3.9 L·min−1, 90% CI 3.6–4.2 L·min−1), and Eaer power was associated with fast performances (P <.001). Conclusion: Faster swimmers were characterized by higher V ˙ O 2 and less time to reach the highest V ˙ O 2 at ∼50 m of the 100-m swim. Anaerobic qualities become more important with age. [ABSTRACT FROM AUTHOR]

Published
2018
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12. Functional Role of Movement and Performance Variability: Adaptation of Front Crawl Swimmers to Competitive Swimming Constraints.

Author

Simbaña Escobar, David, Hellard, Philippe, Pyne, David B., and Seifert, Ludovic

Subjects
THIGH, ATHLETIC ability, STATISTICAL correlation, LIFE skills, SEX distribution, SWIMMING, BODY movement, PHYSIOLOGY
Abstract

To study the variability in stroking parameters between and within laps and individuals during competitions, we compared and modeled the changes of speed, stroke rate, and stroke length in 32 top-level male and female swimmers over 4 laps (L1-L4) in 200-m freestyle events using video-derived 2-dimensional direct linear transformation. For the whole group, speed was greater in L1, with significant decreases across L2, L3, and L4 (1.80 ± 0.10 vs 1.73 ± 0.08; 1.69 ± 0.09; 1.66 ± 0.09 • s-1, P < .05). This variability was attributed to a decrease in stroke length (L2: 2.43 ± 0.19 vs L4: 2.20 ± 0.13 m, P < .05) and an increase in stroke rate (L2: 42.8 ± 2.6 vs L4: 45.4 ± 2.3 stroke • min-1, P < .05). The coefficient of variation and the biological coefficient of variation in speed were greater for male versus female (3.9 ± 0.7 vs 3.1 ± 0.7; 2.9 ± 1.0 vs 2.6 ± 0.7, P < .05) and higher in L1 versus L2 (3.9 ± 1.3 vs 3.1 ± 0.1; 2.9 ± 0.9 vs 2.3 ± 0.7, P < .05). Intra-lap speed values were best represented by a cubic (n = 38), then linear (n = 37) and quadratic model (n = 8). The cubic fit was more frequent for males (43.8%) than females (15.6%), suggesting greater capacity to generate higher acceleration after the turn. The various stroking parameters managements within lap suggest that each swimmer adapts his/her behavior to the race constraints. [ABSTRACT FROM AUTHOR]

Published
2018
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17. Modeling the residual effects and threshold saturation of training: a case study of Olympic swimmers

Author

Hellard, Philippe, Avalos, Marta, Millet, Gregoire, Lacoste, Lucien, Barale, Frederic, and Chatard, Jean-Claude

Subjects
Strengthening exercises -- Research, Swimming -- Research, Health, Sports and fitness
Abstract

Hellard, P., M. Avalos, G. Millet, L. Lacoste, and J.C. Chatard. Modeling the residual effects and threshold saturation of training: A case study of Olympic swimmers. J. Strength Cond. Res. 19(1):67-75. 2005.--The aim of this study was to model the residual effects of training on the swimming performance and to compare a model that includes threshold saturation (MM) with the Banister model (BM). Seven Olympic swimmers were studied over a period of 4 [+ or -] 2 years. For 3 training loads (low-intensity [w.sup.LIT], high-intensity [w.sup.HIT] and strength training [w.sup.ST]), 3 residual training effects were determined: short-term (STE) during the taper phase (i.e., 3 weeks before the performance [weeks 0, 1, and 2]), intermediate-term (ITE) during the intensity phase (weeks 3, 4, and 5), and long-term (LTE) during the volume phase (weeks 6, 7, and 8). ITE and LTE were positive for [w.sup.HIT] and [w.sup.LIT], respectively (p < 0.05). Low-intensity training load during taper was related to performances by a parabolic relationship (p < 0.05). Different quality measures indicated that MM compares favorably with BM. Identifying individual training thresholds may help individualize the distribution of training loads. KEY WORDS. mathematical model, performance, swimming

Published
2005

21. Elite Swimmers’ Training Patterns in the 25 Weeks Prior to Their Season’s Best Performances: Insights Into Periodization From a 20-Years Cohort

Author

Fisiología, Fisiologia, Hellard, Philippe, Avalos Fernandes, Marta, Lefort, Gaelle, Pla, Robin, Mujika Antón, Iñigo, Toussaint, Jean-François, Pyne, David B., Fisiología, Fisiologia, Hellard, Philippe, Avalos Fernandes, Marta, Lefort, Gaelle, Pla, Robin, Mujika Antón, Iñigo, Toussaint, Jean-François, and Pyne, David B.

Abstract

Background: This study investigated the periodization of elite swimmers' training over the 25 weeks preceding the major competition of the season. Methods: We conducted a retrospective observational study of elite male (n = 60) and female (n = 67) swimmers (46 sprint, 81 middle-distance) over 20 competitive seasons (1992-2012). The following variables were monitored: training corresponding to blood lactate <2 mmol.L (-1), 2 to <= 4 mmol.L-1, >4-6 mmol.L-1, >6 mmol.L-1, and maximal swimming speed; general conditioning and maximal strength training hours; total training load (TTL); and the mean normalized volumes for both in-water and dryland workouts. Latent class mixed modeling was used to identify various TTL pattern groups. The associations between pattern groups and sex, age, competition event, Olympic quadrennial year, training contents, and relative performance were quantified. Results: For the entire cohort, similar to 86-90% of the training was swum at an intensity of [La](b) <= 4 mmol.L-1. This training volume was divided into 40-44% at <2 mmol.L-1 and 44-46% at 2 to <= 4 mmol.L-1, leaving 6-9.5% at >4-6 mmol.L-1, and 3.5-4.5% at > 6 mmol.L-1. Three sprint TTL patterns were identified: a pattern with two long similar to 14-15-week macrocycles, one with two similar to 12-13 week macrocycles each composed of a balanced training load, and one with a single stable flat macrocycle. The long pattern elicited the fastest performances and was most prevalent in Olympic quadrennials (i.e., 4 seasons preceding the 2004, 2008, and 2012 Olympic Games). This pattern exhibited moderate week-to-week TTL variability (6 +/- 3%), progressive training load increases between macrocycles, and more training at <= 4 mmol.L(-1 )and >6 mmol.L-1. This fastest sprint pattern showed a waveform in the second macrocycle consisting of two progressive load peaks 10-11 and 4-6 weeks before competition. The stable flat pattern was the slowest and showed low TTL variability (4 +/- 3%), trainin

Published
2019

23. Kinematic and neuro-muscular adaptations following a training program for the underwater dolphin kick

Author

Elipot, Marc, Hellard, Philippe, Puel, Frédéric, Morlier, Julien, Cazalets, Jean-René, Institut national du sport, de l'expertise et de la performance (INSEP), Département d'études et recherches, Fédération Française de Natation (FFN), Performance, Santé, Métrologie, Société - EA 7507 (PSMS), Université de Reims Champagne-Ardenne (URCA), Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Laboratoire Mouvement Adaptation Cognition (MAC), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS), and PUEL, Frédéric

Subjects
[PHYS.MECA.BIOM] Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph], [PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

27. Swimming

Author

Vandenbogaerde, Tom, primary, Derave, Wim, additional, and Hellard, Philippe, additional

Published
2019
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28. Non-targeted metabolomics analyses by mass spectrometry to explore metabolic stress after six training weeks in high level swimmers.

Author

Pla, Robin, Pujos-Guillot, Estelle, Durand, Stéphanie, Brandolini-Bunlon, Marion, Centeno, Delphine, Pyne, David B., Toussaint, Jean-François, and Hellard, Philippe

Subjects
PHYSIOLOGICAL stress, METABOLOMICS, ANTI-inflammatory agents, PHYSICAL training & conditioning, EXERCISE physiology, COMPARATIVE studies, MASS spectrometry, EXERCISE intensity, LACTATES, SWIMMING, CROSSOVER trials, FATIGUE (Physiology)
Abstract

The objective was to compare the metabolic responses of high-level national swimmers to threshold or polarised training. 22 swimmers (n = 12 males and 10 females) participated in a 28-week cross-over intervention study consisting of 2 × 6 period weeks of training. Swimmers were assigned randomly to either training group for the first period: polarised (POL) (81% in energetic zone 1: blood lactate [La]b ≤ 2 mmol.L−1; 4% in zone 2: 2 mmol.L−1 <[La]b ≤ 4 mmol.L−1; 15% in zone 3: [La]b > 4 mmol.L−1) or threshold (THR) (65%/25%/10%). Before and after each training period, urine samples were collected for non-targeted metabolomics analysis. Mixed model analysis was performed on metabolomics data including fatigue class factors and/or training and/or interaction. Ion intensities of 6-keto-decanoylcarnitine (+31%), pregnanediol-3-glucuronide (+81%), P-cresol sulphate (+18%) were higher in the threshold group (P < 0.05) indicating higher glycogenic depletion and inflammation without alteration of the neuroendocrine stress axis. 4-phenylbutanic acid sulphate was 200% higher in less fatigued swimmers (P < 0.01) linking the anti-inflammatory activity at the cell membrane level to the subjective perception of fatigue. This research suggests the importance of replenishing glycogen stores and reducing inflammation during high thresholds training loads. [ABSTRACT FROM AUTHOR]

Published
2021
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29. Exploring variable selection in additive mixed effects models using group lasso

Author

Avalos, Marta, Soret, Perrine, Meza, Cristian, Bertin, Karine, Ren, Hao, Hellard, Philippe, Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Centro de Investigación y Modelamiento de Fenómenos Aleatorios – Valparaíso (CIMFAV), Universidad de Valparaiso [Chile], Université de Technologie de Compiègne (UTC), Fédération Française de Natation (FFN), Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), This research was partially funded by the French Institute of Sport, Expertise and Performance (INSEP) under grant no14r21, Statistical Society of Australia (SSA), Avalos, Marta, Université de Bordeaux ( UB ), Statistics In System biology and Translational Medicine ( SISTM ), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Centro de Investigación y Modelamiento de Fenómenos Aleatorios – Valparaíso ( CIMFAV ), Université de Technologie de Compiègne ( UTC ), Fédération Française de Natation ( FFN ), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Institut national du sport, de l'expertise et de la performance ( INSEP ) -Université Paris Descartes - Paris 5 ( UPD5 ), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], and Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Longitudinal data --- algorithme EM, [ STAT.AP ] Statistics [stat]/Applications [stat.AP], [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], L1-penalty, [STAT.CO] Statistics [stat]/Computation [stat.CO], [ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [ STAT.ME ] Statistics [stat]/Methodology [stat.ME], [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Sport science data, [STAT.CO]Statistics [stat]/Computation [stat.CO], [STAT.ME]Statistics [stat]/Methodology [stat.ME], [ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML], [ STAT.CO ] Statistics [stat]/Computation [stat.CO]
Abstract

International audience; We consider the problem of estimating a high-dimensional additive mixed model for longitudinal data using sparse methods. In this problem, multiple measurements are made on the same subject across time, and then the different sources of variability (intra- and inter-subject variability) and correlation within subjects have to be considered. Also, the relationships between explanatory variables and the outcome arepossibly non linear. In addition, the number of explanatory variables could be larger than the sample size but only a small set of explanatory variables contribute to the response.Several computational approaches for high-dimensional additive modelling for independent data have been developed in the literature. Recently, Amato and colleagues (Stat Methods Appl 2016; s10260-016-0357-8) conducted a comprehensive review of these methods. Efficient regularized estimation procedures for variable selection in nonparametric additive models use basis function approximations. The authors also proposed a reformulation of the estimation problem in terms of group Lasso that allows deducing convergence and asymptotic optimality properties.Only a few works have developed suggestions to analyse high-dimensional longitudinal data using Lasso-type methods in additive mixed model. The resulting estimator depends only on a relatively small number of basis functions, however variable selection is not directly encouraged. In this study we explore the extension of the group Lasso penalty to additive mixed effects models. We discuss computational aspects, including a comparison of group Lasso algorithms implemented through publicly available R codes, the estimation of optimal regularization parameter and linkages between mean and covariance parameter estimation algorithms. We illustrate the interest of such approaches in the analysis of a twenty - year longitudinal study of training practices of elite athletes.

Published
2016

30. Clustering of temporal sport training curves: a comparison of FDA and LDA approaches

Author

Lefort, Gaëlle, Avalos, Marta, Soret, Perrine, David, Pyne, Toussaint, Jean-François, Hellard, Philippe, Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Australian Institute of Sport, Institut national du sport, de l'expertise et de la performance (INSEP), Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Université Paris Descartes - Paris 5 (UPD5), Département d'études et recherches, Fédération Française de Natation (FFN), This research was partially funded by the French Institute of Sport, Expertise and Performance (INSEP) under grant no14r21., Ecole Nationale de la Statistique et de l'Analyse de l'Information ( ENSAI ), Ensai, Ecole Nationale de la Statistique et de l'Analyse de l'Information, Statistics In System biology and Translational Medicine ( SISTM ), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Université de Bordeaux ( UB ), Institut national du sport, de l'expertise et de la performance ( INSEP ), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Université Paris Descartes - Paris 5 ( UPD5 ), Fédération Française de Natation ( FFN ), Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], and Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [ STAT.AP ] Statistics [stat]/Applications [stat.AP], [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, [ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG], Functional data analysis, [ STAT.ME ] Statistics [stat]/Methodology [stat.ME], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Longitudinal data analysis, Sport science data, [STAT.CO]Statistics [stat]/Computation [stat.CO], [STAT.ME]Statistics [stat]/Methodology [stat.ME], [ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML], [ STAT.CO ] Statistics [stat]/Computation [stat.CO]
Abstract

International audience; Functional data analysis (FDA) and longitudinal data analysis (LDA) are the main approaches to analyze repeated measures data (in which multiple measurements are made on the same subject across time). Typically, FDA is applied when the data are dense, assumed to be observed in the continuum, and without noise. LDA is usually applied when data are sparse, possibly with different number of measurements across individuals, and subject to error.In elite sport, the parameters of the training program (intensity, volume, frequency, distribution and duration of high-intensity, recovery, and competition periods) should be manipulated systematically to optimize performance and reduce the risk of injury. Sport training data are recorded densely over time. However, measurements, such as duration of follow-up or duration of the season, vary among subjects. Subject-specific variations may introduce substantial measurement error.The statistical objectives of this study were the following:- First, to review the literature on the most commonly used methods for clustering of time evolution curves with a publicly available R code.- Second, to implement FDA and LDA methods presenting publicly available R code: k-means based on the standard Euclidian distance, a discrete Frèchet distance, and a distance of functions; Gaussian mixture model - based clustering for standard, longitudinal and functional data; and latent class mixed models.- Third, using data from a twenty - year longitudinal study of training practices of elite athletes, to perform a clustering analysis using relevant methods.- Fourth, to compare the results and interpret them. Comparison criteria were mainly based on computational and practical aspects.The practical goal of this project was to identify training profiles and to characterize them to provide relevant tools for supporting decision-making in monitoring athletes' training programs.

Published
2016

31. The Effect of Time of Day on Cold Water Ingestion by High-Level Swimmers in a Tropical Climate.

Author

Hue, Olivier, Monjo, Roland, Lazzaro, Marc, Baillot, Michelle, Hellard, Philippe, Marlin, Laurent, and Jean-Etienne, A.

Subjects
BODY composition, ANALYSIS of variance, ANTHROPOMETRY, BEVERAGES, BODY temperature, CLINICAL trials, COLD (Temperature), CROSSOVER trials, DRINKING (Physiology), ECOLOGY, HEART rate monitoring, HEAT, HUMAN comfort, HUMIDITY, SENSORY perception, QUESTIONNAIRES, STATISTICAL sampling, SKINFOLD thickness, STATISTICS, SWIMMING, TIME, DATA analysis, STATISTICAL significance, PHYSICAL training & conditioning, RANDOMIZED controlled trials, PRE-tests & post-tests, ELITE athletes, EXERCISE intensity, DESCRIPTIVE statistics
Abstract

The authors tested the effect of cold water ingestion during high-intensity training in the morning vs the evening on both core temperature (Tc) and thermal perceptions of internationally ranked long-distance swimmers during a training period in a tropical climate. Nine internationally ranked long-distance swimmers (5 men and 4 women) performed 4 randomized training sessions (2 in the evening and 2 in the morning) with 2 randomized beverages with different temperatures for 3 consecutive days. After a standardized warm-up of 1000 m, the subjects performed a standardized training session that consisted of 10 x 100 m (start every 1'20") at a fixed velocity. The swimmers were then followed for the next 3000 m of the training schedule. Heart rate (HR) was continuously monitored during the 10 x 100 m, whereas Tc, thermal comfort, and thermal sensation (TS) were measured before and after each 1000-m session. Before and after each 1000 m, the swimmers were asked to drink 190 mL of neutral (26.5 ± 2.5°C) or cold (1.3 ± 0.3°C) water packaged in standardized bottles. Results demonstrated that cold water ingestion induced a significant effect on Tc, with a pronounced decrease in the evening, resulting in significantly lower mean Tc and lower mean delta Tc in evening cold (EC) than in evening neutral (EN), concomitant with significantly lower TS in EC than in EN and a significant effect on exercise HR. Moreover, although Tc increased significantly with time in MN, MC, and EN, Tc was stabilized during exercise in EC. To conclude, we demonstrate that a cold beverage had a significant effect on Tc, TS, and HR during training in high-level swimmers in a tropical climate, especially during evening training. [ABSTRACT FROM AUTHOR]

Published
2013
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32. Influence of Angles of Attack, Frequency and Kick Amplitude on Swimmer's Horizontal Velocity During Underwater Phase of a Grab Start.

Author

Houel, Nicolas, Elipot, Marc, André, Frédéric, and Hellard, Philippe

Abstract

The underwater phase of starts represents an important part of the performance in sprint swimming's events. Kinematics variables that swimmers have to take into account to improve their underwater phase of starts are unknown. The aim of this study was to determine the kinematics variables that improve performance during the underwater phase of grab starts. A three-dimensional analysis of the underwater phase of ten swimmers of national level was conducted. Stepwise multiple linear regressions identified the main kinematics variables that influence the horizontal velocity of the swimmer each 0.5 m in the range of 5 to 7.5 m. The results show that the kinematics parameters change during the range of 5 to 7.5 m of the underwater phase of the starts. For this population of swimmers, the results enable proposals of four principles to improve the underwater phase: i) to be streamlined at the beginning of the underwater gliding phase, ii) to start the dolphin kicking after 6 m, iii) to generate propulsive forces using only feet and legs during underwater undulatory swimming, iv) to improve the frequency of underwater undulatory swimming. [ABSTRACT FROM AUTHOR]

Published
2013

33. High-Level Swimmers' Kinetic Efficiency During the Underwater Phase of a Grab Start.

Author

Elipot, Marc, Dietrich, Gilles, Hellard, Philippe, and Houel, Nicolas

Abstract

The purpose of the present work was to study swimmers' efficiency during the underwater phase of the grab start. Eight high-level swimmers participated in this study. They performed two types of start: a regular grab start (with underwater leg propulsion after the glide) and a grab start with no underwater movement (swimmers had to remain in a streamlined position). Four cameras filmed the entire underwater phase of all starts. Nine anatomic landmarks were identified on the swimmers' bodies and their positions were calculated using a modified double plan DLT technique. From these positions and Dempster's anthropometric data, the center of mass position and velocity were also determined. Kinetic energies were also calculated. This velocity and kinetic energies for the two types of start were compared. Swimmers began underwater leg propulsion 1.69 m too soon. The global and internal energies were significantly higher for the start with underwater leg propulsion. Nevertheless, swimmers' velocities were equivalent for both starts. These results suggest that the swimmers did not use the underwater phase of the start efficiently: By kicking too soon, they did not succeed in producing higher velocities and thus wasted energy. [ABSTRACT FROM AUTHOR]

Published
2010

34. A comparison of unsupervised curve classification methods for sport training data

Author

Lefort, Gaëlle, Avalos, Marta, Soret, Perrine, David, Pyne, Toussaint, Jean-François, Hellard, Philippe, Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Australian Institute of Sport, Institut national du sport, de l'expertise et de la performance (INSEP), Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Université Paris Descartes - Paris 5 (UPD5), Fédération Française de Natation (FFN), This research was partially funded by the French Institute of Sport, Expertise and Performance (INSEP) under grant no14r21., The International Society for NonParametric Statistics (ISNPS), Ecole Nationale de la Statistique et de l'Analyse de l'Information ( ENSAI ), Ensai, Ecole Nationale de la Statistique et de l'Analyse de l'Information, Statistics In System biology and Translational Medicine ( SISTM ), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Université de Bordeaux ( UB ), Institut national du sport, de l'expertise et de la performance ( INSEP ), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Université Paris Descartes - Paris 5 ( UPD5 ), Fédération Française de Natation ( FFN ), Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Avalos, Marta

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], [ STAT.AP ] Statistics [stat]/Applications [stat.AP], [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [STAT.CO] Statistics [stat]/Computation [stat.CO], [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG], Functional data analysis, [ STAT.ME ] Statistics [stat]/Methodology [stat.ME], [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Longitudinal data analysis, Sport science data, [STAT.CO]Statistics [stat]/Computation [stat.CO], [STAT.ME]Statistics [stat]/Methodology [stat.ME], [ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML], [ STAT.CO ] Statistics [stat]/Computation [stat.CO]
Abstract

International audience; Achieving peak performance at a specified time is the primary goal of athletes’ training programs. To optimize performance and reduce the risk of injury, a comprehensive list of training program parameters (e.g. intensity, volume, frequency, distribution, duration and type) requires careful management. This work focuses on clustering of time evolution curves of training measurements.Training data are recorded densely over time. However, duration of follow-up and duration of the seasons vary among subjects. Also, subject-specific variation can induce substantial error. Functional data analysis (FDA) and longitudinal data analysis (LDA) are the main approaches to analyze repeated measures data (in which multiple measurements are made on the same subject across time). Typically, FDA is applied when the data are dense, assumed to be observed in the continuum, and a function of time. LDA is usually applied when data are sparse, possibly with different number of measurements across individuals, and subject to error. We compared several FDA and LDA methods implemented through publicly available R code: k-means based on the standard Euclidian distance, a discrete Fréchet distance [2], and a functional distance [1]; Gaussian mixture model–based clustering for standard [4], longitudinal [5] and functional [3] data; and latent class mixed models [6]. We discuss advantages and limitations including computational and practical aspects.References[1] Febrero-Bande, M. and Oviedo de la Fuente, M. (2012). Statistical computing in functional data analysis: the R package fda.usc. Journal of Statistical Software, 51, 1–28.[2] Genolini, C. and Falissard, B. (2011). Kml : A package to cluster longitudinal data. Computer Methods and Programs in Biomedicine.[3] Jacques, J. and Preda, C. (2013). Funclust: A curves clustering method using functional random variables density approximation. Neurocomputing, 112, 164–171.[4] Lebret, R., Iovleff, S., Langrognet, F., Biernacki, C., Celeux, G., and Govaert, G. (2014). Rmixmod: The R package of the model–based unsupervised, supervised and semi–supervised classification mixmod library. Journal of Statistical Software.[5] McNicholas, P. D. and Murphy, T. B. (2010). Model–based clustering of longitudinal data. Canadian Journal of Statistics, 38, 153–168.[6] Proust-Lima, C., Philipps, V., and Liquet, B. (2015). Estimation of extended mixed models using latent classes and latent processes: the R package lcmm. Technical report, University of Bordeaux. arXiv:1503.00890v2.

Published
2016

36. Training-Related Risk of Common Illnesses in Elite Swimmers over a Four-Year Period

Author

Hellard, Philippe, Avalos, Marta, Guimaraes, Fanny, Toussaint, Jean-François, David, Pyne, Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Fédération Française de Natation (FFN), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA), Université Paris Descartes - Paris 5 (UPD5), Australian Institute of Sport, Institut national du sport, de l'expertise et de la performance (INSEP)-Université Paris Descartes - Paris 5 (UPD5), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Fédération Française de Natation ( FFN ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Statistics In System biology and Translational Medicine ( SISTM ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Institut National des Sciences Appliquées - Toulouse ( INSA Toulouse ), Institut National des Sciences Appliquées ( INSA ), and Université Paris Descartes - Paris 5 ( UPD5 )

Subjects
education, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract

International audience; PURPOSE: To investigate the relationship between sport training and the risk of common illnesses: upper respiratory tract and pulmonary infections (URTPI), muscular affections (MA), and all-type pathologies in highly trained swimmers.METHODS: Twenty-eight French professional swimmers were monitored weekly for four years. Training variables included 1/in-water and dryland intensity levels: low-load, high-load, resistance, maximal strength, and general conditioning (expressed as the percentage of the maximal load performed by each subject, at each intensity level over the study period); and 2/training periods: moderate, intensive, taper, competition and post-competition. Illnesses were diagnosed by a sports physician using a standardized questionnaire. Mixed-effects logistic regression analyses were used to model odds ratios for the association between common illnesses and training variables, adjusted for sport season, semi-season (summer or winter), age, competition level, sex and history of recent events, while controlling for heterogeneity among swimmers.RESULTS: The risk of common illnesses was significantly higher in winter months, for national swimmers (for URTPI), and in cases of history of recent event (notably for MA). The odds of URTPI increased 1.08 [95% confidence interval (CI) 1.01-1.16] and 1.10 (95% CI 1.01-1.19) times for every 10% increase in resistance and high-load trainings, respectively. The odds of MA increased by 1.49 (95% CI 1.14-1.96) and 1.63 (95% CI 1.20-2.21) for each 10% increase in high-load, and general conditioning trainings, respectively. The odds of illnesses were 50-70% significantly higher during intensive training periods.CONCLUSION: Particular attention must be paid to illness prevention strategies during periods of intensive training, particularly in the winter months or in case of recent medical episode.

Published
2015

37. Ventilatory, metabolic and kinematic responses in sprint versus distance swimmers

Author

Hellard, Philippe, Leprêtre, Pierre-Marie, Avalos, Marta, Seifert, Ludovic, Toussaint, Jean-François, Hausswirth, Christophe, Saunders, Philo, David, Pyne, Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Adaptations Physiologiques à l'Exercice et Réadaptation à l'effort - UR UPJV 3300 (APERE), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d’études des transformations des activités physiques et sportives (CETAPS), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut de Recherche Interdisciplinaire Homme et Société (IRIHS), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Université Paris Descartes - Paris 5 (UPD5), Institut national du sport et de l'éducation physique (INSEP), Australian Institute of Sport, Institut national du sport, de l'expertise et de la performance (INSEP)-Université Paris Descartes - Paris 5 (UPD5), UFR STAPS, Laboratoire APERE, EA 3300, Université de Picardie Jules Verne (UPJV), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Université de Picardie Jules Verne ( UPJV ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Statistics In System biology and Translational Medicine ( SISTM ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Centre d’études des transformations des activités physiques et sportives ( CETAPS ), Université de Rouen Normandie ( UNIROUEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Institut de Recherche Interdisciplinaire Homme et Société ( IRIHS ), Normandie Université ( NU ) -Normandie Université ( NU ) -Université de Rouen Normandie ( UNIROUEN ), Normandie Université ( NU ), Université Paris Descartes - Paris 5 ( UPD5 ), and Institut national du sport et de l'éducation physique ( INSEP )

Subjects
[ SDV ] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], human activities
Abstract

International audience; The aim of this study was to compare the speed, oxygen uptake (VO2 consumption), blood lactate concentration ([La]b), and stroke rate (SR) in sprint and middle-distance swimmers. Seven male elite middle-distance swimmers (performance level=89% of the world record) and seven male sprint swimmers (performance level=88% of the world record) were recruited. Ventilatory, metabolic and kinematic parameters were obtained during a 6 x 300-m incremental swimming exercise to exhaustion. VO2 kinetics were compared between groups using a 500-m interval training set (IT-500) swum at the lactate threshold (LT). Speed at VO2max was faster for the middle-distance swimmers (1.51 ± 0.02 m.s-1) than the sprinters (1.34 ± 0.07 m.s-1). Speed at LT was also faster for the middle-distance swimmers (3.1 ± 1.2 mmol.L-1; v LT = 1.46 ± 0.01 m•s-1, equivalent to 96.7 ± 0.5% of vVO2max) than the sprinters (4.5 ± 1.5 mmol.L-1; v LT = 1.22 ± 0.06 m•s-1, 91 ± 1.9% of vVO2max; P < 0.01). The middle-distance swimmers had a higher stroke rate at LT (36.7 ± 4.5 vs. 30.3 ± 0.7 s.min-1) and consumed a larger VO2max fraction (95 ± 2 vs. 84 ± 5% of VO2max; P < 0.01). A significant positive correlation was observed between ΔVE and ΔSR (r² = 0.93, P < 0.01) in the middle-distance swimmers during the IT-500, whereas a negative relationship was observed with Δstroke length (r² = 0.81, P < 0.01). The middle-distance swimmers were typically 10-15% faster at the lactate threshold and at the maximal oxygen uptake. In contrast, the blood lactate concentration was 40% higher in the sprint swimmers but the stroke rate was 15% lower at the lactate threshold.

Published
2014

38. Comparing methods for summarizing a training load in prediction models of swimming performance

Author

Scordia, Charlotte, Avalos, Marta, Hellard, Philippe, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Fédération Française de Natation (FFN), Bruce Mason, Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Statistics In System biology and Translational Medicine ( SISTM ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Fédération Française de Natation ( FFN ), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Institut national du sport, de l'expertise et de la performance (INSEP)-Université Paris Descartes - Paris 5 (UPD5)

Subjects
[ SDV ] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], education
Abstract

International audience; Introduction. Training quantifications are valuable for monitoring and prescribing elite swimmers’ training and are indispensable in mathematical models that attempt to accurately predict performance. Modelling the association of training with performance raises an important issue: how should we account for volumes at different training intensities? Mujika et al. (1996) constructed a training load by adding weighted (by a priori constants representing energetic intensities) volumes from each intensity. Avalos et al. (2003) computed a training load as the sum of normalised training intensities. Here we compared the predictive accuracy of these methods to others based on: a/ alternative normalisations, b/ summary scores derived from data, and c/ machine learning techniques, with recognised predictive qualities, such as PLS.Methods. Training volumes at eight intensity levels (in kilometres and minutes per week, for in-water and dry-land workouts, respectively) and performances in competition of 138 professional French swimmers were collected during 20 seasons. Training intensities were determined using measurements of blood lactate concentrations. We assumed that swimmers may react differently to the same training and over time, thus we used mixed-effects models adjusted for sex, age, swimming distance and event specialty. The comparison criterion was the cross-validated prediction error.Results. Summary scores for three training loads (low-intensity/high-intensity/dry-land workouts) with data derived weights showed the best results (mean cross-validated prediction error ± SD were 0.60±0.89, 0.50±0.62 and 0.10±0.19 for sprint, mid- and long-distances, respectively). However, cross-validated prediction errors were close relative to their variances, which were high.Conclusions. The use of complex machine learning techniques did not lead to more accuracy in predicting performance. Although data derived scores showed the lowest prediction error, the statistical variability was too high for being conclusive. A possible explanation is that the lactate sensitivity to extraneous factors (mode of exercise, technique quality of training, diet or sleep quality prior to test) and the subject-specific variations in lactate thresholds introduce not negligible measurement error. As practical recommendation, we suggest completing lactate measurements with athlete/coach questionnaires to better assess the physiological stress associated with the training load. Also, errors-in-variables models might be more appropriated.

Published
2014

39. How the swimmer could improve his track start using new Olympic plot

Author

Houel, Nicolas, Charliac, A, Rey, Jean-Lionel, Hellard, Philippe, and Institut national du sport, de l'expertise et de la performance (INSEP)

Subjects
swimming start, [SHS.SPORT]Humanities and Social Sciences/Sport, kinematic, [SHS.SPORT.PS]Humanities and Social Sciences/Sport/Sport physiology, anthropometric, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2010

40. Modélisation des relations entre les charges d'entraînement et les pathologies infectieuses chez 28 nageurs élites durant 3 saisons

Author

Hellard, Philippe, Guimaraes, Fanny, Avalos, Marta, Toussaint, Jean-François, Département d'études et recherches, Fédération Française de Natation (FFN), Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Institut national du sport et de l'éducation physique (INSEP), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fédération Française de Natation ( FFN ), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Institut national du sport et de l'éducation physique ( INSEP ), Institut National des Sciences Appliquées - Toulouse ( INSA Toulouse ), Institut National des Sciences Appliquées ( INSA ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Institut National des Sciences Appliquées (INSA), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées, and Avalos, Marta

Subjects
[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

National audience; Introduction Une surcharge d'entraînement ainsi que des épreuves compétitives peuvent provoquer un surentraînement, caractérisé par un affaiblissement des défenses immunitaires et une augmentation des pathologies infectieuses (Gleeson, 2006, 2007). L'objectif de cette recherche est de modéliser les relations entre périodes d'entraînement et pathologies infectieuses chez 28 sujets (14 hommes et 14 femmes), dont 8 nageurs de niveau international et 20 nageurs de niveau national, suivis longitudinalement de 2003 à 2006. Méthodes Les symptômes suivants ont été rapportés chaque semaine par un médecin: infections ORL et pulmonaires, affections musculaires et tout autre type. A partir d'un test progressif jusqu'à épuisement (Mujika et al., 1996), les charges d'entraînement dans l'eau ont été quantifiées en deux catégories: les charges de basse intensité (en dessous du seuil lactique) et celles de haute intensité au dessus du seuil (HI). Les charges d'entraînement à sec ont été quantifiées en trois catégories: les charges de force maximale, d'endurance de force (EF) et de préparation physique générale. Le modèle logistique étudie l'association entre le risque d'infection et les charges d'entraînement dans l'eau, à sec et les variables temporelles (saison sportive, période hivernale et estivale), tout en ajustant pour les caractéristiques individuelles (âge, sexe, niveau national ou international). Les mesures longitudinales impliquant des corrélations inter et intra individuelles, des modèles logistiques à effets mixtes ont été alors utilisés. Les coefficients ont été estimés en utilisant la procédure NLMIXED de SAS version 9.1 (Cary, NC). La sélection des modèles a été réalisée par l'utilisation du critère d'Akaike, un estimateur de l'erreur de prédiction. Pour chaque modèle final, les intervalles de confiance ont été calculés et le pouvoir discriminant a été étudié par la courbe caractéristique des opérations du récepteur (ROC) ainsi que l'aire sous la courbe (AUC). Résultats Le risque d'infection ORL ou pulmonaire est plus élevé en hiver et pour les nageurs de niveau national comparativement aux nageurs de niveau international. Le risque d'affections musculaires a été plus élevé chez les femmes. Le risque d'infection est plus élevé durant les périodes de reprise et de pleine charge. Les charges HI et EF augmentent le risque d'infection. Pour tous les modèles, les variables sont toutes significatives, p

Published
2009

41. Modélisation des relations entre la variabilité de la fréquence cardiaque et les pathologies infectieuses chez 18 nageurs élites durant 3 saisons. Effets de la saison et du niveau de performance

Author

Hellard, Philippe, Guimaraes, Fanny, Avalos, Marta, Toussaint, Jean-François, Institut de recherche biomédicale et d’épidémiologie du sport (IRMES - EA 7329), Université Paris Descartes - Paris 5 (UPD5)-Institut national du sport, de l'expertise et de la performance (INSEP), Département d'études et recherches, Fédération Française de Natation (FFN), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées, Institut national du sport, de l'expertise et de la performance (INSEP), Avalos, Marta, Institut National des Sciences Appliquées (INSA), Institut de recherche biomédicale et d’épidémiologie du sport ( IRMES - EA 7329 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut national du sport, de l'expertise et de la performance ( INSEP ), Fédération Française de Natation ( FFN ), Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Institut National des Sciences Appliquées - Toulouse ( INSA Toulouse ), Institut National des Sciences Appliquées ( INSA ), Institut national du sport, de l'expertise et de la performance ( INSEP ), and Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)

Subjects
[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

National audience; Introduction La réduction du risque d'infection durant les périodes d'entraînement les plus intensives comme durant les périodes de compétitions optimisent les effets de l'entraînement et les performances (Gleeson, 2007). Or, il a été montré que des perturbations du profil autonome dans le sens d'une prédominance sympathique favorisaient diverses pathologies gastro-intestinales (Furlan et al., 2008) ou de la sphère laryngopharyngée (Carpenter et al., 2008). De telles perturbations de la régulation autonome ont été mises en évidence dans les périodes de surentraînement (Pichot et al., 2002). L'objectif de cette recherche est de modéliser les relations entre l'activité autonome, estimée par la mesure de la variabilité de la fréquence cardiaque (VFC), et les pathologies infectieuses chez 18 nageurs élites (10 hommes et 8 femmes) suivis longitudinalement de 2003 à 2006. Méthodes Les infections ORL et pulmonaires, les affections musculaires, et tous les autres types d'infections ont été rapportés chaque semaine par un médecin. Les mesures de VFC ont été réalisées dans des conditions similaires durant huit minutes en décubitus et en orthostatisme. La VFC a été évaluée suivant les recommendations de la Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Une analyse des enregistrements des intervalles R-R a été réalisée par la méthode de Poincaré donnant les deux indicateurs standard SD1 et SD2. Le software Nevrokard (Medistar, Ljubjana, Slovenia) a été utilisé pour quantifier la densité de la puissance spectrale du signal par une transformée de Fourrier rapide. Modélisation statistique Le risque d'infection est analysé une fonction des variables VFC, des variables temporelles (saison sportive, période hivernale et estivale) et des caractéristiques individuelles (âge, sexe, niveau de compétition). Les coefficients sont estimés par la procédure NLMIXED de SAS. Les modèles avec les plus petits critères d'Akaike, dont les variables étaient significatives (p≤0.05) et les intervalles de confiance raisonnables, ont été sélectionnés. Résultats Le risque d'infection ORL ou pulmonaire est plus élevé en hiver et pour les nageurs de niveau national comparativement aux nageurs de niveau international. Le risque d'infection est associé à une baisse de SD1 et à une augmentation de PT en décubitus. La décroissance de HF en orthostatisme est reliée à une augmentation du risque d'infection de toutes catégories une semaine plus tard. L'augmentation de LF, la décroissance de HFnu et de SD1 en orthostatisme a augmenté le risque d'affection musculaire. Le risque d'infection est significativement plus élevé lors d'un déplacement de la balance autonome vers une prédominance sympathique.

Published
2009

42. Training Analysis and the Modelling of Relations between Training Volumes and Performance: Interpretation of Results in Light of the New Paradigms of Complexity

Author

Hellard, Philippe, Gerville-Réache, Léo, Fauquet, c, Avalos, Marta, Menaud, A, Fédération Française de Natation (FFN), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB), Laboratoire Cultures, Éducation, Sociétés - Didactique et Anthropologie des Enseignements Scientifiques et Langagiers (LACES DAESL), and Université Bordeaux Segalen - Bordeaux 2

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2002

43. Effets de différentes modalités de récupération sur les paramètres sanguins, énergétiques et de performance musculaire, à l'issue de ballets réalisés par les nageuses synchronisées en Equipe de France

Author

Schaal, Karine, Le Meur, Yann, Bieuzen, François, Le Van, Philippe, Filliard, Jean-Robert, Volondat, Marielle, Cozzolino, Christophe, Petit, Odile, Hellard, Philippe, Toussaint, Jean-François, Hausswirth, Christophe, Schaal, Karine, Le Meur, Yann, Bieuzen, François, Le Van, Philippe, Filliard, Jean-Robert, Volondat, Marielle, Cozzolino, Christophe, Petit, Odile, Hellard, Philippe, Toussaint, Jean-François, and Hausswirth, Christophe

Abstract

Cette étude est la première à mettre en avant les contraintes physiologiques associées à l'exécution d'un ballet de natation synchronisée de niveau international. Nous démontrons qu'une telle performance demande un effort physique important, avec un engagement maximal de la production d'énergie aérobie et de larges contributions anaérobies, exacerbées par les contraintes des phases d'apnées de ces performances.. Ces résultats mettent donc en exergue l'importance d'une récupération post-exercice adéquate afin de maintenir les capacités physiques des nageuses dans le cadre de performances répétées à court terme. L'un des résultats majeurs de cette étude est l'identification des effets bénéfiques de la cryothérapie corps entier sur les paramètres de récupération métaboliques et neurovégétatifs, puisque c'est la première fois que l'efficacité de cette technique est testée dans ces conditions d'exercices maximaux répétés. Sur le plan de la récupération du système nerveux autonome, la cryothérapie corps entier s'avère extrêmement efficace, lorsqu'utilisée peu de temps après un exercice maximal engendrant une forte activité sympathique et une suppression quasi-totale de l'activité parasympathique au niveau cardiaque. Alors que plusieurs études ont récemment démontré que l'immersion en eau froide était une méthode efficace permettant d'améliorer la réactivation vagale post-exercice, la cryothérapie corps entier augmente celle-ci au-delà de l'activité parasympathique pré-exercice. En termes d'applications pratiques, les données confirment que dans le cadre de performances maximales répétées, les méthodes de récupération actives et de cryostimulation corps entier sont à préconiser, suivie des protocoles d'immersion contrastée, alors que la récupération entièrement passive est à éviter. Dans l'aspect pratique de la programmation de 'entraînement, la cryothérapie corps entier n'est pas aussi simple à intégrer dans le quotidien des athlètes que la récupération active, et cette d

Published
2012

44. Modélisation des relations « entraînement - performance en natation

Author

GERVILLE-RÉACHE, Léo, HELLARD, Philippe, MENAUD, A, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), and Fédération Française de Natation (FFN)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2000

47. Living high–training low: effect on erythropoiesis and aerobic performance in highly-trained swimmers

Author

Robach, Paul, primary, Schmitt, Laurent, additional, Brugniaux, Julien V., additional, Roels, Belle, additional, Millet, Grégoire, additional, Hellard, Philippe, additional, Nicolet, Gérard, additional, Duvallet, Alain, additional, Fouillot, Jean-Pierre, additional, Moutereau, Stéphane, additional, Lasne, Françoise, additional, Pialoux, Vincent, additional, Olsen, Niels V., additional, and Richalet, Jean-Paul, additional

Published
2005
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