Publications by authors named "Thiago Ventura"
Article Synopsis
- The study compared peak oxygen uptake (V̇O2peak), peak heart rate (HRpeak), and peak O2 pulse in hand-cyclists with spinal cord injury during two different tests on the same day.
- Eight competitive hand-cyclists performed a maximal incremental test and a verification test at 100% V̇O2peak speed, finding that V̇O2peak was significantly higher in the verification test.
- Despite similar HRpeak values in both tests, the verification test showed a higher peak O2 pulse, indicating its importance for accurately measuring V̇O2peak in this population.
Introduction: This study aimed to analyze the effect of caffeine (CAF) intake on pulmonary oxygen uptake (V˙O2) kinetics, muscle fatigue, and physiological and perceptual parameters during severe-intensity cycling exercise.
Methods: Twelve physically active men (age: 26 ± 5 years; V˙O2peak: 46.7 ± 7.
The effect of caffeine chewing gum on muscle performance and fatigue after severe-intensity exercise: isometric vs. dynamic assessments in trained cyclists.
Eur J Appl Physiol
September 2024
Article Synopsis
- * Fifteen cyclists performed four testing sessions with two cycling bouts each, using either caffeinated gum or placebo in a double-blind setup, but showed no significant difference in performance between the two types of gum after exercise.
- * Results indicated that caffeinated gum did not effectively reduce muscle force decline, and moderate correlations suggested caution in linking isometric force measurements directly to fatigue in dynamic activities.
No Combined Effect of Caffeinated Chewing Gum and Priming Exercise on Oxygen Uptake and Muscle Near-Infrared Spectroscopy-Derived Kinetics: A Double-Blind Randomized Crossover Placebo-Controlled Trial in Cyclists.
Int J Sport Nutr Exerc Metab
November 2024
This study aimed to investigate the effects of caffeine ingestion by chewing gum (GUMCAF) combined with priming exercise on pulmonary oxygen uptake (V˙O2) and near-infrared spectroscopy-derived muscle oxygen extraction (HHb + Mb) kinetics during cycling performed in a severe-intensity domain. Fifteen trained cyclists completed four visits: two under a placebo gum (GUMPLA) and two under GUMCAF ingestion. Each visit consisted of two square-wave cycling bouts at Δ70 intensity (70% of difference between the V˙O2 at first ventilatory threshold and V˙O2max) with duration of 6 min each and 5 min of passive rest between the bouts.
View Article and Find Full Text PDFReliability and Validity of Cycling Sprint Performance at Isolinear Mode Without Torque Factor: A Preliminary Study in Well-Trained Male Cyclists.
Res Q Exerc Sport
September 2024
Article Synopsis
- - This study compared cycling performance using two sprint modes: isolinear (ISO) and isovelocity (ISO), with 20 trained male cyclists completing multiple short sprints on a specialized ergometer.
- - Results showed that while torque (T) was significantly greater in the ISO mode, maximum cadence (C) was higher in the other ISO mode, with both modes yielding similar power outputs (P) and optimal cadence power (OPT).
- - The findings suggest that a single test in ISO mode is effective for assessing muscle fatigue during cycling, demonstrating good consistency and acceptable variability in results.
This study aimed to assess the predictive capability of different critical power (CP) models on cycling exercise tolerance in the severe- and extreme-intensity domains. Nineteen cyclists (age: 23.0 ± 2.
View Article and Find Full Text PDFThe purpose of this study was to verify the heart rate variability (HRV) and heart rate (HR) kinetics during the fundamental phase in different intensity domains of cycling exercise. Fourteen males performed five exercise sessions: (1) maximal incremental cycling test; (2) two rest-to-exercise transitions for each intensity domain, that is, heavy (Δ30) and severe (Δ60) domains. HRV markers (SD1 and SD2) and HR kinetics in the fundamental phase were analyzed by first-order exponential fitting.
View Article and Find Full Text PDFAutomated acoustic recognition of birds is considered an important technology in support of biodiversity monitoring and biodiversity conservation activities. These activities require processing large amounts of soundscape recordings. Typically, recordings are transformed to a number of acoustic features, and a machine learning method is used to build models and recognize the sound events of interest.
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