Abstract：
OBJECTIVE: While various fitness tests have been developed to assess physical performances, it is unclear how these tests are affected by differences, such as, in morphological and neural factors. This study was aimed to investigate associations between individual differences in physical fitness tests and neuromuscular properties.
METHODS: One hundred and thirty-three young adults participated in various general physical fitness tests and neuromuscular measurements. The appendicular skeletal muscle mass (ASM) was estimated by bioelectrical impedance analysis. Echo intensity (EI) was evaluated from the vastus lateralis. During submaximal knee extension force, high-density surface electromyography of the vastus lateralis was recorded and individual motor unit firings were detected. Y-intercept (i-MU) and slope (s-MU) from the regression line between the recruitment threshold and motor unit firing rate were calculated.
RESULTS: Stepwise multiple regression analyses revealed that knee extension strength could be explained (adjusted R2 = 0.712) by ASM (β = 0.723), i-MU (0.317), EI (- 0.177), and s-MU (0.210). Five-sec stepping could be explained by ASM (adjusted R2 = 0.212). Grip strength, side-stepping, and standing broad jump could be explained by ASM and echo intensity (adjusted R2 = 0.686, 0.354, and 0.627, respectively). Squat jump could be explained by EI (adjusted R2 = 0.640). Counter-movement jump could be explained by EI and s-MU (adjusted R2 = 0.631). On the other hand, i-MU and s-MU could be explained by five-sec stepping and counter-movement jump, respectively, but the coefficients of determination were low (adjusted R2 = 0.100 and 0.045).
CONCLUSIONS: Generally developed physical fitness tests were mainly explained by morphological factors, but were weakly affected by neural factors involved in performance.
METHODS: One hundred and thirty-three young adults participated in various general physical fitness tests and neuromuscular measurements. The appendicular skeletal muscle mass (ASM) was estimated by bioelectrical impedance analysis. Echo intensity (EI) was evaluated from the vastus lateralis. During submaximal knee extension force, high-density surface electromyography of the vastus lateralis was recorded and individual motor unit firings were detected. Y-intercept (i-MU) and slope (s-MU) from the regression line between the recruitment threshold and motor unit firing rate were calculated.
RESULTS: Stepwise multiple regression analyses revealed that knee extension strength could be explained (adjusted R2 = 0.712) by ASM (β = 0.723), i-MU (0.317), EI (- 0.177), and s-MU (0.210). Five-sec stepping could be explained by ASM (adjusted R2 = 0.212). Grip strength, side-stepping, and standing broad jump could be explained by ASM and echo intensity (adjusted R2 = 0.686, 0.354, and 0.627, respectively). Squat jump could be explained by EI (adjusted R2 = 0.640). Counter-movement jump could be explained by EI and s-MU (adjusted R2 = 0.631). On the other hand, i-MU and s-MU could be explained by five-sec stepping and counter-movement jump, respectively, but the coefficients of determination were low (adjusted R2 = 0.100 and 0.045).
CONCLUSIONS: Generally developed physical fitness tests were mainly explained by morphological factors, but were weakly affected by neural factors involved in performance.
摘要：
目标：虽然已经开发了各种体能测试来评估身体表现，目前尚不清楚这些测试如何受到差异的影响，例如,形态和神经因素。这项研究旨在调查体质测试中的个体差异与神经肌肉特性之间的关联。
方法：一百三十三个年轻人参加了各种一般的体能测试和神经肌肉测量。通过生物电阻抗分析估计阑尾骨骼肌质量（ASM）。从股外侧肌评估回声强度（EI）。在膝盖伸展力次最大时,记录股外侧肌的高密度表面肌电图，并检测到单个运动单位放电。计算了募集阈值与运动单位射击率之间的回归线的Y截距（i-MU）和斜率（s-MU）。
结果：逐步多元回归分析显示，膝关节伸展强度可以通过ASM（β=0.723）来解释（调整后的R2=0.712），i-MU(0.317)，EI（-0.177），和s-MU(0.210)。5秒步进可以用ASM(调整后的R2=0.212)来解释。握力,侧步，站立跳跃可以用ASM和回波强度（分别调整后的R2=0.686、0.354和0.627）来解释。下蹲跳跃可以用EI(调整后的R2=0.640)来解释。逆运动跳跃可以用EI和s-MU(调整后的R2=0.631)来解释。另一方面,i-MU和s-MU可以用五秒步进和反移动跳跃来解释，分别,但测定系数较低(调整后的R2=0.100和0.045)。
结论：通常发达的体能测试主要由形态因素解释，但受到与表现有关的神经因素的微弱影响。
方法：一百三十三个年轻人参加了各种一般的体能测试和神经肌肉测量。通过生物电阻抗分析估计阑尾骨骼肌质量（ASM）。从股外侧肌评估回声强度（EI）。在膝盖伸展力次最大时,记录股外侧肌的高密度表面肌电图，并检测到单个运动单位放电。计算了募集阈值与运动单位射击率之间的回归线的Y截距（i-MU）和斜率（s-MU）。
结果：逐步多元回归分析显示，膝关节伸展强度可以通过ASM（β=0.723）来解释（调整后的R2=0.712），i-MU(0.317)，EI（-0.177），和s-MU(0.210)。5秒步进可以用ASM(调整后的R2=0.212)来解释。握力,侧步，站立跳跃可以用ASM和回波强度（分别调整后的R2=0.686、0.354和0.627）来解释。下蹲跳跃可以用EI(调整后的R2=0.640)来解释。逆运动跳跃可以用EI和s-MU(调整后的R2=0.631)来解释。另一方面,i-MU和s-MU可以用五秒步进和反移动跳跃来解释，分别,但测定系数较低(调整后的R2=0.100和0.045)。
结论：通常发达的体能测试主要由形态因素解释，但受到与表现有关的神经因素的微弱影响。
