Investigating the effect of bouncing type on the physiological demands of trampolining

Trampoline Stiffness Estimation by Using Robotic System for Quantitative Evaluation of Jumping Exercises

Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate factors such as stiffness, elements influencing jump dynamics, and user safety. Previous studies assessing trampoline characteristics had limitations in performing repetitive experiments at various locations on the trampoline. Therefore, this research introduces a robotic system equipped with foot-shaped jigs to evaluate trampoline stiffness and quantitatively measure exercise effects. This system, through automated, repetitive movements at various locations on the trampoline, accurately measures the elastic coefficient and vertical forces. The robot maneuvers based on the coordinates of the trampoline, as determined by its torque and position sensors. The force sensor measures data related to the force exerted, along with the vertical force data at X, Y, and Z coordinates. The model's accuracy was evaluated using linear regression based on Hooke's Law, with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient Squared (R-squared) metrics. In the analysis including only the distance between X and the foot-shaped jigs, the average MAE, RMSE, and R-squared values were 17.9702, 21.7226, and 0.9840, respectively. Notably, expanding the model to include distances in X, Y, and between the foot-shaped jigs resulted in a decrease in MAE to 15.7347, RMSE to 18.8226, and an increase in R-squared to 0.9854. The integrated model, including distances in X, Y, and between the foot-shaped jigs, showed improved predictive capability with lower MAE and RMSE and higher R-squared, indicating its effectiveness in more accurately predicting trampoline dynamics, vital in fitness and rehabilitation fields.

Nutritional intake and anthropometric characteristics are associated with endurance performance and markers of low energy availability in young female cross-country skiers

BACKGROUND

Low energy availability (LEA) can have negative performance consequences, but the relationships between LEA and performance are poorly understood especially in field conditions. In addition, little is known about the contribution of macronutrients to long-term performance. Therefore, the aim of this study was to evaluate if energy availability (EA) and macronutrient intake in a field-based situation were associated with laboratory-measured performance, anthropometric characteristics, blood markers, training volume, and/or questionnaire-assessed risk of LEA in young female cross-country (XC) skiers. In addition, the study aimed to clarify which factors explained performance.

METHODS

During a one-year observational study, 23 highly trained female XC skiers and biathletes (age 17.1 ± 1.0 years) completed 3-day food and training logs on four occasions (September-October, February-March, April-May, July-August). Mean (±SD) EA and macronutrient intake from these 12 days were calculated to describe yearly overall practices. Laboratory measurements (body composition with bioimpedance, blood hormone concentrations, maximal oxygen uptake (VO_2max), oxygen uptake (VO₂) at 4 mmol·L^-1 lactate threshold (OBLA), double poling (DP) performance (time to exhaustion), counter movement jump (height) and the Low Energy Availability in Females Questionnaire (LEAF-Q)) were completed at the beginning (August 2020, M₁) and end of the study (August 2021, M₂). Annual training volume between measurements was recorded using an online training diary.

RESULTS

The 12-day mean EA (37.4 ± 9.1 kcal·kg FFM^-1·d^-1) and carbohydrate (CHO) intake (4.8 ± 0.8 g·kg^-1·d^-1) were suboptimal while intake of protein (1.8 ± 0.3 g·kg^-1·d^-1) and fat (31 ± 4 E%) were within recommended ranges. Lower EA and CHO intake were associated with a higher LEAF-Q score (r  = 0.44, p  = 0.042; r  = 0.47, p  = 0.026). Higher CHO and protein intake were associated with higher VO_2max (r  = 0.61, p  = 0.005; r  = 0.54, p  = 0.014), VO₂ at OBLA (r  = 0.63, p  = 0.003; r  = 0.62, p  = 0.003), and DP performance at M₂ (r  = 0.42, p  = 0.051; r  = 0.44, p  = 0.039). Body fat percentage (F%) was negatively associated with CHO and protein intake (r = -0.50, p  = 0.017; r = -0.66, p  = 0.001). Better DP performance at M₂ was explained by higher training volume (R²  = 0.24, p  = 0.033) and higher relative VO_2max and VO₂ at OBLA at M₂ by lower F% (R²  = 0.44, p  = 0.004; R²  = 0.47, p  = 0.003). Increase from M₁ to M₂ in DP performance was explained by a decrease in F% (R²  = 0.25, p  = 0.029).

CONCLUSIONS

F%, and training volume were the most important factors explaining performance in young female XC skiers. Notably, lower F% was associated with higher macronutrient intake, suggesting that restricting nutritional intake may not be a good strategy to modify body composition in young female athletes. In addition, lower overall CHO intake and EA increased risk of LEA determined by LEAF-Q. These findings highlight the importance of adequate nutritional intake to support performance and overall health.