Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes.

Use of muscle oxygen saturation (SmO2) has been validated as a performance factor during incremental exercise with portable near-infrared stereoscopy (NIRS) technology. However, there is little knowledge about the use of SmO2 to identify training zones. The objective of this study was to evaluate the metabolic zones by SmO2: maximum lipid oxidation zone (Fatmax), ventilatory thresholds (VT1 and VT2) and maximum aerobic power (MAP) during a graded exercise test (GXT). Forty trained cyclists and triathletes performed a GXT. Output power (W), heart rate (HR), oxygen consumption (VO2), energy expenditure (kcal/min) and SmO2 were measured. Data were analysed using the ANOVA test, ROC curves and multiple linear regressions. Significance was established at p ≤ 0.05. SmO2 decreases were observed from baseline (LB) to Fatmax (Δ = -16% p < 0.05), Fatmax to VT1 (Δ = -16% p < 0.05) and VT1 to VT2 (Δ = -45% p < 0.01). Furthermore, SmO2 together with weight, HR and output power have the ability to predict VO2 and energy expenditure by 89% and 90%, respectively. We conclude that VO2 and energy expenditure values can be approximated using SmO2 together with other physiological parameters and SmO2 measurements can be a complementary parameter to discriminate aerobic workload and anaerobic workload in athletes.

Monitoring Muscle Oxygen Asymmetry as a Strategy to Prevent Injuries in Footballers.

Purpose: It has been hypothesized that sports injury risk is explained by muscle metabolism. The objective was to evaluate the muscle oxygen saturation slopes (ΔSmO2 slopes) and muscle oxygenation asymmetry (MO2Asy) at rest and to study their associations with injuries during the pre-season. Methods: A total of 16 male and 10 female footballers participated in this study. Injuries were diagnosed and classified by level of severity during the pre-season. The workload was also evaluated using the rate of perceived exertion × training time, from which the accumulated loads. The SmO2 was measured at rest in the gastrocnemius muscle using the arterial occlusion method in the dominant and non-dominant legs. The repeated measures ANOVA, relative risk, and binary logistic regression were applied to assess the probability of injury with SmO2 and workload. Results: Higher MO2Asy and ΔSmO2 Slope 2 were found among footballer who suffered high-severity injuries and those who presented no injuries. In addition, an MO2Asy greater than 15% and an increase in accumulated load were variables that explained a greater probability of injury. Conclusion: This study presents the new concept of muscle oxygenation asymmetry in sports science and its possible application in injury prevention through the measurement of SmO2 at rest.

Tent versus Mask-On Acute Effects during Repeated-Sprint Training in Normobaric Hypoxia and Normoxia.

Repeated sprint in hypoxia (RSH) is used to improve supramaximal cycling capacity, but little is known about the potential differences between different systems for creating normobaric hypoxia, such as a chamber, tent, or mask. This study aimed to compare the environmental (carbon dioxide (CO2) and wet-globe bulb temperature (WGBT)), perceptual (pain, respiratory difficulty, and rate of perceived exertion (RPE)), and external (peak and mean power output) and internal (peak heart rate (HRpeak), muscle oxygen saturation (SmO2), arterial oxygen saturation (SpO2), blood lactate and glucose) workload acute effects of an RSH session when performed inside a tent versus using a mask. Twelve well-trained cyclists (age = 29 ± 9.8 years, VO2max = 70.3 ± 5.9 mL/kg/min) participated in this single-blind, randomized, crossover trial. Participants completed four sessions of three sets of five repetitions × 10 s:20 s (180 s rest between series) of all-out in different conditions: normoxia in a tent (RSNTent) and mask-on (RSNMask), and normobaric hypoxia in a tent (RSHTent) and mask-on (RSHMask). CO2 and WGBT levels increased steadily in all conditions (p < 0.01) and were lower when using a mask (RSNMask and RSHMask) than when inside a tent (RSHTent and RSNTent) (p < 0.01). RSHTent presented lower SpO2 than the other three conditions (p < 0.05), and hypoxic conditions presented lower SpO2 than normoxic ones (p < 0.05). HRpeak, RPE, blood lactate, and blood glucose increased throughout the training, as expected. RSH could lead to acute conditions such as hypoxemia, which may be exacerbated when using a tent to simulate hypoxia compared to a mask-based system.

Muscle Oxygen Desaturation and Re-Saturation Capacity Limits in Repeated Sprint Ability Performance in Women Soccer Players: A New Physiological Interpretation.

Muscle oxygen consumption could provide information on oxidative metabolism in women soccer players. Therefore, the objective of this study was to analyze muscle oxygenation dynamics during repeated sprint ability (RSA): (8 sprint × 20 s recovery) by near-infrared spectroscopy (NIRS). The sample was made up of 38 professional women soccer players. To measure the external load, the best time, worst time, average time, individual speed, sprint decrement, and power were assessed. In connection with the internal load, the desaturation (sprint) and re-saturation (recovery) rates, as well as the oxygen extraction (∇%SmO2) in the gastrocnemius muscle and maximum heart rate (%HRmax) were measured. A repeated measures statistic was applied based on the inter-individual response of each subject from the baseline versus the other sprints, with linear regression and nonlinear regression analyses between variables. There was an increase in the SmO2: desaturation rate after four sprints (Δ = 32%), in the re-saturation rate after six sprints (Δ = 89%), and in ∇%SmO2 after four sprints (Δ = 72.1%). There was a linear association between the rates of desaturation and re-saturation relationships and the worst time (r = 0.85), and a non-linear association between ∇%SmO2 and speed (r = 0.89) and between ∇%SmO2 and the sprint decrease (r = 0.93). The progressive increase in SmO2 during RSA is a performance limitation to maintain a high speed; it depends on the capacity of fatigue resistance. Therefore, monitoring the muscle oxygenation dynamics could be a useful tool to evaluate the performance in women soccer players.

Control del entrenamiento con datos GPS y medidas subjetivas de fatiga y recuperación en futbolistas hondureños durante un periodo preparatorio para los Juegos Olímpicos de Tokio 2020/2021 / Training Monitoring With GPS Data and Subjective Measures of Fatigue and Recovery in Honduran Soccer Players During a Preparatory Period for Tokyo 2020/2021 Olympic Games / Monitoramento do treinamento com dados GPS e medidas subjetivas de fadiga e recuperação dos jogadores de futebol hondurenhos durante um período preparatório para os Jogos Olímpicos de Tóquio 2020/2021

Resumen: Introducción: El control de cargas de entrenamiento es importante para optimizar el rendimiento. Por lo tanto, se deben documentar metodologías que mejoren la preparación de selecciones nacionales en eventos como los juegos olímpicos. Objetivo: Determinar si los datos del GPS en combinación con medidas subjetivas de bienestar, fatiga y recuperación son apropiados para el control de las cargas durante un periodo preparatorio para los Juegos Olímpicos. Metodología: Participaron 22 jugadores profesionales sub-23 durante 5 microciclos y 27 sesiones de entrenamiento. Se recopilaron datos de carga externa a través de un sistema global de posicionamiento (GPS): Distancia total (DT), zonas de rendimiento Z0 (0-15 km/h), Z1 (15.1-18 km/h), Z2 (18.1-24 km/h), Z3 (>24.1 km/h)), velocidad máxima (Vmax (km/h)), aceleraciones (>2.5m/s2) y desaceleraciones (<2.5m/s2). También, se obtuvo la carga interna a través de medidas subjetivas de percepción del esfuerzo (RPE), calidad de la recuperación (TQR), predisposición para entrenar (RTT%) derivada de las variables de calidad del sueño, dolor muscular, niveles de energía, estado de ánimo, estrés, calidad de la alimentación y la salud. Luego se calculó la ratio subjetiva de fatiga-recuperación (F-R). Se aplicó un test ANOVA, análisis de componentes principales (ACP) y una regresión múltiple lineal. Resultados: Las variables DT (p=0.00 TE=0.22), Z0 (p= 0.00 TE=0.08), Z2 (p=0.00 TE= 0.05), Vmax (p=0.00 TE=0.42), suma de aceleración y deceleración (p=0.00 TE=0.08) y valores relativos de la carga/min (p=0.00 TE=0.17) se identificaron como variables más sensibles al cambio de la carga entre microciclos. El RTT% y ratio subjetivo F-R mostraron un tamaño del efecto moderado (p=0.04 TE=0.06 y p=0.06 TE=0.06), pero fueron sensibles al cambio entre los microciclos. El ACP extrajo 15 variables GPS y 11 variables subjetivas que explicaron el 78% de la varianza de la carga de entrenamiento. Conclusión: Utilizar datos GPS junto con medidas subjetivas implicadas en la fatiga-recuperación puede ser una buena estrategia para el control de la carga de entrenamiento en futbolistas.

Abstract: Background: Training control is essential to optimize performance. Therefore, methodologies that improve the preparation of national teams in events such as the Olympic Games should be documented. Purpose: To determine whether GPS data in combination with subjective measures of well-being, fatigue and recovery are appropriate for load monitoring during a preparatory period for the Olympic Games. Methodology: Twenty-two under-23 professional players participated during 5 micro-cycles and 27 training sessions. External load data was collected via a global positioning system (GPS): Total distance (DT), performance zones Z0 (0-15 km/h), Z1 (15.1-18 km/h), Z2 (18.1 -24 km/h), Z3 (>24.1 km/h), maximum speed (km/h), accelerations (>2.5m/s.) and decelerations (<2.5m/s.). Also, internal load was obtained through subjective measures of Rating Perceived Exertion (RPE), Total Quality Recovery (TQR), Readiness to Train (RTT%) obtained from the sleep quality, muscle pain, energy levels, mood, stress, food quality and health. The subjective rate of fatigue-recovery (F-R) was then calculated. An ANOVA test, Principal Component Analysis (PCA) and multiple linear regression were applied. Results: the variables DT (p=0.00 ES=0.22), Z0 (p= 0.00 TE=0.08), Z2 (p=0.00 ES= 0.05), maximum speed (p= 0.00 ES=0.42), sum of acceleration and deceleration (p=0.00 ES=0.08) and values relative to load/min (p=0.00 ES=0.17) were identified as variables more sensitive to load change between micro-cycles. RTT% and subjective rate F-R showed a moderate effect size (p=0.04 ES=0.06 and p=0.06 ES=0.06), but were sensitive to change between micro-cycles. PCA extracted 15 GPS variables and 11 subjective variables that explained 78% of the training load variance. Conclusion: Using GPS data together with subjective measures involved in fatigue-recovery may be a good strategy to control training load in footballers.

Resumo: Introdução: O monitoramento das cargas de treinamento é importante para otimizar o desempenho. Portanto, as metodologias devem ser documentadas para melhorar a preparação das equipes nacionais para eventos como os Jogos Olímpicos. Objetivo: Determinar se os dados GPS em combinação com medidas subjetivas de bem-estar, fadiga e recuperação são apropriados para o monitoramento da carga durante um período preparatório para os Jogos Olímpicos. Metodologia: 22 jogadores profissionais U-23 participaram durante 5 microciclos e 27 sessões de treinamento. Os dados de carga externa foram coletados através de um sistema de posicionamento global (GPS): distância total (DT), zonas de desempenho Z0 (0- 15 km/h), Z1 (15,1-18 km/h), Z2 (18,1-24 km/h), Z3 (>24,1 km/h), velocidade máxima (Vmax (km/h)), acelerações (>2,5m/ s2) e desacelerações (<2,5m/s2). Além disso, a carga interna foi obtida através de medidas subjetivas de percepção do esforço (RPE), qualidade de recuperação (TQR), predisposição para o treinamento (RTT%) derivada das variáveis de qualidade do sono, dor muscular, níveis de energia, humor, estresse, qualidade alimentar e saúde. Posteriormente a taxa subjetiva de fadiga-recuperação (F-R) foi calculada. Um teste ANOVA, análise de componentes principais (ACP) e regressão linear múltipla foram aplicados. Resultados: As variáveis DT (p=0,00 TE=0,22), Z0 (p= 0,00 TE=0,08), Z2 (p=0,00 TE= 0,05), Vmax (p=0,00 TE=0,42), soma de aceleração e desaceleração (p=0,00 TE=0,08) e valores de carga relativa/min (p=0,00 TE=0,17) foram identificadas como as variáveis mais sensíveis à mudança de carga entre microciclos. RTT% e a relação F-R subjetiva mostraram tamanho de efeito moderado (p=0,04 TE=0,06 e p=0,06 TE=0,06 TE=0,06), mas foram sensíveis à mudança entre microciclos. O ACP extraiu 15 variáveis GPS e 11 variáveis subjetivas que explicaram 78% da variância na carga de treinamento. Conclusão: O uso de dados GPS junto com medidas subjetivas envolvidas na fadiga#recuperação pode ser uma boa estratégia para o monitoramento da carga de treinamento em jogadores de futebol.