Frontiers in public health · 2025
An investigation of the load-velocity relationship between flywheel eccentric and barbell training methods.
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Zhu Ziwei, Chen Jiayong, Sun Ruize, Wang Renchen, He Jiaxin, Zhang Wenfeng, Lin Weilong, Li Duanying
Аннотация
OBJECTIVE: Flywheel resistance training (FRT) is a training modality for developing lower limb athletic performance. The relationship between FRT load parameters and barbell squat loading remains ambiguous in practice, resulting in experience-driven load selection during training. Therefore, this study investigates optimal FRT loading for specific training goals (maximal strength, power, muscular endurance) by analyzing concentric velocity at varying barbell 1RM percentages (%1RM), establishes correlations between flywheel load, velocity, and %1RM, and integrates force-velocity profiling to develop evidence-based guidelines for individualized load prescription.
METHODS: Thirty-nine participants completed 1RM barbell squats to establish submaximal loads (20-90%1RM). Concentric velocities were monitored via linear-position transducer (Gymaware) for FRT inertial load quantification, with test-retest measurements confirming protocol reliability. Simple and multiple linear regression modeled load-velocity interactions and multivariable relationships, while Pearson's r and R2 quantified correlations and model fit. Predictive equations estimated inertial loads (kg·m2), supported by ICC (2, 1) and CV assessments of relative/absolute reliability.
RESULTS: A strong inverse correlation (r = -0.88) and high linearity (R2 = 0.78) emerged between rotational inertia and velocity. The multivariate model demonstrated excellent fit (R2 = 0.81) and robust correlation (r = 0.90), yielding the predictive equation: y = 0.769-0.846v + 0.002 kg.
CONCLUSION: The strong linear inertial load-velocity relationship enables individualized load prescription through regression equations incorporating velocity and strength parameters. While FRT demonstrates limited efficacy for developing speed-strength, its longitudinal periodization effects require further investigation. Optimal FRT loading ranges were identified: 40-60%1RM for strength-speed, 60-80%1RM for power development, and 80-100% + 1RM for maximal strength adaptations.
METHODS: Thirty-nine participants completed 1RM barbell squats to establish submaximal loads (20-90%1RM). Concentric velocities were monitored via linear-position transducer (Gymaware) for FRT inertial load quantification, with test-retest measurements confirming protocol reliability. Simple and multiple linear regression modeled load-velocity interactions and multivariable relationships, while Pearson's r and R2 quantified correlations and model fit. Predictive equations estimated inertial loads (kg·m2), supported by ICC (2, 1) and CV assessments of relative/absolute reliability.
RESULTS: A strong inverse correlation (r = -0.88) and high linearity (R2 = 0.78) emerged between rotational inertia and velocity. The multivariate model demonstrated excellent fit (R2 = 0.81) and robust correlation (r = 0.90), yielding the predictive equation: y = 0.769-0.846v + 0.002 kg.
CONCLUSION: The strong linear inertial load-velocity relationship enables individualized load prescription through regression equations incorporating velocity and strength parameters. While FRT demonstrates limited efficacy for developing speed-strength, its longitudinal periodization effects require further investigation. Optimal FRT loading ranges were identified: 40-60%1RM for strength-speed, 60-80%1RM for power development, and 80-100% + 1RM for maximal strength adaptations.