Study on the differences in peripheral fatigue responses elicitation effects of bench press training with different loads and tempos based on electromyography and motion sensors

基于肌电图和运动传感器,研究不同负荷和节奏的卧推训练对周围疲劳反应诱发效果的差异

阅读:1

Abstract

OBJECTIVE: This study aimed to investigate the effects of bench press training with different loads (60% 1RM vs. 80% 1RM) and tempos (maximal velocity X/0/X/0 vs. medium tempo 2/0/2/0) on peripheral fatigue responses in bodybuilders, assessing the specific roles of neuromuscular activation, metabolic stress, and kinetic performance. METHODS: Ten experienced male bodybuilders performed four training protocols to exhaustion in a randomized crossover design. Electromyography (EMG) was used to record muscle activation (normalized as %MVIC) and spectral shifts (Median Frequency - MDF) from the pectoralis major, anterior deltoid, and triceps brachii muscles. Biochemical assessment involved measuring blood lactate concentrations pre- and post-exercise to quantify metabolic stress. Motion sensors (Vmaxpro) were employed to capture barbell kinematics-including mean velocity (MV), peak velocity (PV), mean power (MP), peak power (PP), and time under tension (TUT)-providing direct measures of neuromuscular performance and fatigue-related velocity loss. RESULTS: A significant interaction between load and tempo was found for all fatigue markers (p < 0.05). The combination of high load and fast tempo (80% 1RM, X/0/X/0) induced the most pronounced peripheral fatigue, evidenced by the highest muscle activation (%MVIC) and blood lactate levels, coupled with the greatest declines in MDF (indicating neuromuscular fatigue), velocity, and power output. CONCLUSION: The interaction of load and tempo critically determines the pattern and magnitude of acute peripheral fatigue. High-load fast-tempo training elicits multifaceted fatigue across neuromuscular, metabolic, and performance domains, whereas a high-load medium-tempo protocol results in less fatigue despite longer TUT. These findings provide a scientific basis for precise fatigue management in resistance programming.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。