Training studies involving competitive runners and road cyclists have shown substantial gains in sprint and endurance performance when sessions of high-intensity interval training were added to their usual training in the competitive phase of a season. Further research has shown large performance benefits in sprint and endurance power (7 - 9%) when cyclists combined explosive single-leg jumps with cycling-specific high-intensity interval training during a competitive season. The aim of the present study was to assess the contribution of the jumps to the gains in performance in competitive cyclists in a randomized control trial.The training protocol for the control group was based on previous experimental work in which the control group (n=8) completed cycle specific interval training followed by a series of explosive single-leg jumps. The experimental group (n=7) carried out the same cycle specific interval training but did not participate in the explosive single-leg jumps. While the current study did not use a true control group, the investigation was carried out in the knowledge that a combination of high intensity interval cycling and explosive single-leg jumps causes changes positive changes in performance. Participants took part in 10 x 30-min sessions consisting four sets of high intensity intermittent cycling (4 x 30-s maximum efforts at 50 - 60 min-1 alternating with 30-s recovery). Between each set of 4 x 30 s sprints the control (ballistic) group carried out one set of explosive single-leg jumps (20 for each leg), while the experimental (continuous) group cycled for 20 s at 50 - 60 min-1.Before and after the training period all cyclists completed an incremental peak power test for assessment of VO2max, lactate threshold, exercise economy and peak power, a 30 s Wingate sprint test and a 20 km time-trial. Relative to the control group the percent mean changes (±90% confidence limits) in the experimental group were: power at 4-mM lactate, -4.2 (±6.3); VO2max, -3.1 (±3.7); mean time-trial power, -0.7 (± 4.7); peak incremental power, -1.7; (±5.0); power at 80% max heart rate, -2.8; (±5.6); Wingate peak power, -4.2; (±7.8). We conclude that high-intensity training may improve performance but the combination of high-intensity training and explosive resistance training in the competitive phase is likely to produce greater gains in trained cyclists than high intensity cycling alone.

Training studies involving competitive runners and road cyclists have shown substantial gains in sprint and endurance performance when sessions of high-intensity interval training were added to their usual training in the competitive phase of a season. Further research has shown large performance benefits in sprint and endurance power (7 - 9%) when cyclists combined explosive single-leg jumps with cycling-specific high-intensity interval training during a competitive season. The aim of the present study was to assess the contribution of the jumps to the gains in performance in competitive cyclists in a randomized control trial.The training protocol for the control group was based on previous experimental work in which the control group (n=8) completed cycle specific interval training followed by a series of explosive single-leg jumps. The experimental group (n=7) carried out the same cycle specific interval training but did not participate in the explosive single-leg jumps. While the current study did not use a true control group, the investigation was carried out in the knowledge that a combination of high intensity interval cycling and explosive single-leg jumps causes changes positive changes in performance. Participants took part in 10 x 30-min sessions consisting four sets of high intensity intermittent cycling (4 x 30-s maximum efforts at 50 - 60 min-1 alternating with 30-s recovery). Between each set of 4 x 30 s sprints the control (ballistic) group carried out one set of explosive single-leg jumps (20 for each leg), while the experimental (continuous) group cycled for 20 s at 50 - 60 min-1.Before and after the training period all cyclists completed an incremental peak power test for assessment of VO2max, lactate threshold, exercise economy and peak power, a 30 s Wingate sprint test and a 20 km time-trial. Relative to the control group the percent mean changes (±90% confidence limits) in the experimental group were: power at 4-mM lactate, -4.2 (±6.3); VO2max, -3.1 (±3.7); mean time-trial power, -0.7 (± 4.7); peak incremental power, -1.7; (±5.0); power at 80% max heart rate, -2.8; (±5.6); Wingate peak power, -4.2; (±7.8). We conclude that high-intensity training may improve performance but the combination of high-intensity training and explosive resistance training in the competitive phase is likely to produce greater gains in trained cyclists than high intensity cycling alone.

Les Interfaces Cerveau-Ordinateur basées sur l’Imagerie Mentale (IM-ICO) permettent auxutilisateurs d’interagir uniquement via leur activité cérébrale, grâce à la réalisation de tâchesd’imagerie mentale. Cette thèse se veut contribuer à l’amélioration des IM-ICO dans le but deles rendre plus utilisables. Les IM-ICO sont extrêmement prometteuses dans de nombreuxdomaines allant de la rééducation post-AVC aux jeux-vidéo. Malheureusement, leurdéveloppement est freiné par le fait que 15 à 30% des utilisateurs seraient incapables de lescontrôler. Nombre de travaux se sont focalisés sur l’amélioration des algorithmes de traitementdu signal. Par contre, l’impact de l’entraînement des utilisateurs sur leur performance estsouvent négligé. Contrôler une IM-ICO nécessite l’acquisition de compétences et donc unentraînement approprié. Or, malgré le fait qu’il ait été suggéré que les protocolesd’entraînement actuels sont théoriquement inappropriés, peu d’efforts sont mis en oeuvre pourles améliorer. Notre principal objectif est de comprendre et améliorer l’apprentissage des IMICO.Ainsi, nous cherchons d’abord à acquérir une meilleure compréhension des processussous-tendant cet apprentissage avant de proposer une amélioration des protocolesd’entraînement afin qu’ils prennent en compte les facteurs cognitifs et psychologiquespertinents et qu’ils respectent les principes issus de l’ingénierie pédagogique. Nous avonsainsi défini 3 axes de recherche visant à investiguer l’impact (1) de facteurs cognitifs, (2) de lapersonnalité et (3) du feedback sur la performance. Pour chacun de ces axes, nous décrivonsd’abord les études nous ayant permis de déterminer les facteurs impactant la performance ;nous présentons ensuite le design et la validation de nouvelles approches d’entraînementavant de proposer des perspectives de travaux futurs. Enfin, nous proposons une solution quipermettrait d’étudier l’apprentissage de manière mutli-factorielle et dynamique : un systèmetutoriel intelligent. / Mental-imagery based brain-computer interfaces (MI-BCIs) enable users to interact with theirenvironment using their brain-activity alone, by performing mental-imagery tasks. This thesisaims to contribute to the improvement of MI-BCIs in order to render them more usable. MIBCIsare bringing innovative prospects in many fields, ranging from stroke rehabilitation tovideo games. Unfortunately, most of the promising MI-BCI based applications are not yetavailable on the public market since an estimated 15 to 30% of users seem unable to controlthem. A lot of research has focused on the improvement of signal processing algorithms.However, the potential role of user training in MI-BCI performance seems to be mostlyneglected. Controlling an MI-BCI requires the acquisition of specific skills, and thus anappropriate training procedure. Yet, although current training protocols have been shown tobe theoretically inappropriate, very little research is done towards their improvement. Our mainobject is to understand and improve MI-BCI user-training. Thus, first we aim to acquire a betterunderstanding of the processes underlying MI-BCI user-training. Next, based on thisunderstanding, we aim at improving MI-BCI user-training so that it takes into account therelevant psychological and cognitive factors and complies with the principles of instructionaldesign. Therefore, we defined 3 research axes which consisted in investigating the impact of(1) cognitive factors, (2) personality and (3) feedback on MI-BCI performance. For each axis,we first describe the studies that enabled us to determine which factors impact MI-BCIperformance; second, we describe the design and validation of new training approaches; thethird part is dedicated to future work. Finally, we propose a solution that could enable theinvestigation of MI-BCI user-training using a multifactorial and dynamic approach: an IntelligentTutoring System.