Artistic swimming is a highly demanding sport, both physically and mentally, which, combined with the high training volume associated with this activity, generates a significant risk of injury. The objective of this study was to analyse the incidence, characteristics, and injury burden in female artistic swimmers. The sample consisted of 390 unique swimmers (121 followed across both seasons; 511 athlete-seasons) classified into four age categories: U12 (< 12 years; n = 215), U16 (12–14 years; n = 102), U19 (15–18 years; n = 33), and Senior/Master (≥ 19 years; n = 40). Injuries were monitored and recorded in four clubs over two seasons (2023–2025) and in two clubs over one season (2024–2025). A total of 70 injuries were recorded in 65 swimmers. In the U12 category, 24 injuries were recorded (incidence: 0.23 injuries/1,000 h [95
Inspired oxygen fraction (FiO₂) may alter the internal physiological cost of supramaximal interval training. This randomized exploratory active-comparator study compared functional adaptations to hyperoxic versus hypoxic Tabata-format high-intensity interval training (HIIT). Twenty-three physically active men completed 3 weeks of supramaximal Tabata-format HIIT (3 sessions·week⁻¹; 8 × 20 s with 10 s recovery) under hyperoxia (FiO₂ = 0.60, n = 13) or hypoxia (FiO₂ = 0.16, n = 10). Intensity was initially prescribed from baseline CPET-derived Wmax and operationally regulated using heart rate to maintain the intended internal cardiovascular strain. V̇O₂max was the primary outcome; ventilatory thresholds, peak blood lactate, perceived exertion, heart-rate outcomes, and available workload records were secondary or exploratory outcomes. V̇O₂max increased from 37.77 ± 8.67 to 41.46 ± 8.41 mL·kg⁻¹·min⁻¹ in hyperoxia and from 38.30 ± 9.91 to 39.80 ± 9.80 mL·kg⁻¹·min⁻¹ in hypoxia, with a larger baseline-adjusted improvement under hyperoxia. VT1 increased from 175.0 ± 52.0 to 213.5 ± 46.3 W in hyperoxia and from 160.0 ± 47.4 to 170.0 ± 48.3 W in hypoxia. VT2 increased from 232.7 ± 51.4 to 263.5 ± 40.3 W in hyperoxia and from 207.5 ± 55.3 to 222.5 ± 49.2 W in hypoxia. Peak lactate decreased from 9.58 ± 1.37 to 8.81 ± 1.47 mmol·L⁻¹ in hyperoxia but increased from 8.93 ± 0.84 to 9.25 ± 0.75 mmol·L⁻¹ in hypoxia. Wmax increased from 278.8 ± 55.8 to 334.6 ± 45.1 W in hyperoxia and from 247.5 ± 73.1 to 282.5 ± 63.5 W in hypoxia. Hyperoxic and hypoxic Tabata-format HIIT elicited divergent functional response profiles within this internally regulated two-arm protocol. Hyperoxia was associated with broader aerobic functional improvements and lower post-exercise peak lactate, whereas hypoxia produced smaller aerobic gains and a higher post-exercise peak lactate response. These findings should be interpreted as exploratory because of the small sample, absence of a normoxic comparator, and limited session-level external-load and heart-rate recording. ClinicalTrials.gov, NCT07551869. Retrospectively registered on 5 April 2026.
Objective assessment of localized muscle fatigue may support exercise prescription, rehabilitation monitoring, and sports performance management. Surface electromyography (sEMG) reflects neuromuscular activation, whereas B-mode and Doppler ultrasonography provide complementary information on muscle morphology and vascular response. This study evaluated training-dependent biceps brachii fatigue using ultrasound and sEMG and examined whether combined dynamic recordings improved fatigue-state classification. Forty healthy men were allocated to an advanced resistance-training group (n = 20) or a novice group (n = 20). Participants performed seated right-arm 10-kg dumbbell curls until voluntary exhaustion. Because the same absolute load represented different relative intensities across participants and groups, training-status comparisons were interpreted accordingly. Biceps brachii muscle thickness, anterior circumflex humeral artery peak systolic velocity (PSV), sEMG root mean square (RMS), and median frequency (MDF) were measured at baseline, moderate fatigue, and exhaustion. Stage-matched ultrasound video and sEMG recordings from 35 artifact-free participants were evaluated by participant-level five-fold internal cross-validation. Advanced trainees completed more repetitions than novices (16.3 ± 2.7 vs. 13.3 ± 2.3 repetitions, p < 0.001). Baseline-to-exhaustion muscle-thickness change was smaller in advanced trainees than in novices (12.69 ± 4.67
To develop an interpretable machine learning model based on biomechanical measurement parameters to predict peak anterior cruciate ligament (ACL) force during side-cutting maneuvers, thereby providing an assessment method for sports training and monitoring. A total of 204 male football and basketball athletes were recruited. Kinematic, kinetic, and electromyographic parameters during side-cutting maneuvers were extracted using the Qualisys optical motion capture system, force plates, and surface electromyography. Machine learning algorithms were used for model training and testing to predict peak ACL force, and Shapley Additive Explanations (SHAP) were employed to interpret feature values. The Extreme Gradient Boosting (XGBoost) model demonstrated high fitting performance (R² = 0.929), with low overall deviation (RMSE = 0.051) and prediction error (MAE = 0.032). Global SHAP importance analysis indicated that knee flexion angle (KFA), hamstring-to-quadriceps activation ratio (H/Q), hip flexion angle (HFA), knee valgus moment (KVM), ankle valgus angle (AVA), hip adduction angle (HAA), and anterior tibial shear force (ASF) were the key features for predicting peak ACL force. The SHAP importance values of KFA (0.07), H/Q (0.05), HFA (0.03), KVM (0.02), and AVA (0.02) showed relatively high contributions, demonstrating strong predictive ability. The increase in peak ACL force during side-cutting maneuvers is essentially the result of the coupling of dynamic postural control mechanical loads and neuromuscular effects. The machine learning model integrating multidimensional indicators achieved high accuracy, improved the predictive capability of peak ACL force in practical applications, and provided an interpretation for the comprehensive analysis of peak ACL force.
We aimed to develop contemporary reference values among recreationally trained and strength-interested individuals for the squat, bench press, and deadlift, and describe sex- and age-related patterns in estimated relative strength. This cross-sectional study analysed user-reported data collected between 1 January and 31 December 2024 by Strength Level Limited. Submissions reported sex, age, body mass, load lifted, and repetitions completed. Inclusion criteria were age ≥ 12 years, entries for all three lifts on the same day from the same hashed IP address, and ≤ 15 repetitions. Estimated one-repetition maximums (e1RMs) were derived using Brzycki and Epley equations with interpolation between 8 and 10 repetitions. Relative strength was calculated as e1RM divided by body mass (kg/kgbody mass), and percentile norms were generated separately for males and females across age groups. Data from 64,457 males and 10,435 females were included. All lifts were right-skewed, with higher e1RMs and greater variability observed in males. In males, relative strength was greater in young adulthood than adolescence, and lower in middle-aged and older adults. In females, relative strength was similar in adolescence and young adulthood, with lower values observed in middle-aged and older adults. For example, median relative squat strength was 1.77 and 1.38 kg/kgbody mass in young and older males, respectively, and 1.30 and 0.99 kg/kgbody mass in young and older females, respectively. These findings provide contemporary benchmarks for squat, bench press, and deadlift strength among recreational and strength-interested individuals.
