Padulo Johnny, Rampichini Susanna, Borrelli Marta, Buono Daniel Maria, Doria Christian, Esposito Fabio
Department of Biomedical Sciences for Health (SCIBIS), Università degli Studi di Milano, 20133 Milan, Italy.
IRCCS Galeazzi Orthopedic Institute, 20161 Milan, Italy.
J Funct Morphol Kinesiol. 2023 Nov 8;8(4):158. doi: 10.3390/jfmk8040158.
Gait variability (GV) is a crucial measure of inconsistency of muscular activities or body segmental movements during repeated tasks. Hence, GV might serve as a relevant and sensitive measure to quantify adjustments of walking control. However, it has not been clarified whether GV is associated with walking speed, a clarification needed to exploit effective better bilateral coordination level. For this aim, fourteen male students (age 22.4 ± 2.7 years, body mass 74.9 ± 6.8 kg, and body height 1.78 ± 0.05 m) took part in this study. After three days of walking 1 km each day at a self-selected speed (SS) on asphalt with an Apple Watch S. 7 (Apple, Cupertino, CA, USA), the participants were randomly evaluated on a treadmill at three different walking speed intensities for 10 min at each one, SS - 20%/SS + 20%/ SS, with 5 min of passive recovery in-between. Heart rate (HR) was monitored and normalized as %HR, while the rate of perceived exertion (RPE) (CR-10 scale) was asked after each trial. Kinematic analysis was performed, assessing the Contact Time (CT), Swing Time (ST), Stride Length (SL), Stride Cycle (SC), and Gait Variability as Phase Coordination Index (PCI). RPE and HR increased as the walking speed increased ( = 0.005 and = 0.035, respectively). CT and SC decreased as the speed increased ( = 0.0001 and = 0.013, respectively), while ST remained unchanged ( = 0.277). SL increased with higher walking speed ( = 0.0001). Conversely, PCI was 3.81 ± 0.88% (high variability) at 3.96 ± 0.47 km·h, 2.64 ± 0.75% (low variability) at SS (4.94 ± 0.58 km·h), and 3.36 ± 1.09% (high variability) at 5.94 ± 0.70 km·h ( = 0.001). These results indicate that while the metabolic demand and kinematics variables change linearly with increasing speed, the most effective GV was observed at SS. Therefore, SS could be a new methodological approach to choose the individual walking speed, normalize the speed intensity, and avoid a gait pattern alteration.
步态变异性(GV)是重复任务期间肌肉活动或身体节段运动不一致性的关键指标。因此,GV可能是量化步行控制调整的一个相关且敏感的指标。然而,GV是否与步行速度相关尚未明确,而这一问题的明确对于更好地利用有效的双侧协调水平至关重要。为此,14名男学生(年龄22.4±2.7岁,体重74.9±6.8千克,身高1.78±0.05米)参与了本研究。在连续三天使用苹果手表S7(苹果公司,美国加利福尼亚州库比蒂诺)以自选速度(SS)在沥青路面上每天步行1公里后,参与者在跑步机上以三种不同的步行速度强度进行随机评估,每种强度持续10分钟,即SS - 20%/SS + 20%/SS,中间有5分钟的被动恢复时间。监测心率(HR)并将其标准化为%HR,同时在每次试验后询问自觉用力程度(RPE)(CR - 10量表)。进行运动学分析,评估接触时间(CT)、摆动时间(ST)、步长(SL)、步幅周期(SC)以及作为相位协调指数(PCI)的步态变异性。随着步行速度增加,RPE和HR升高(分别为 = 0.005和 = 0.035)。随着速度增加,CT和SC降低(分别为 = 0.0001和 = 0.013),而ST保持不变( = 0.277)。SL随着步行速度提高而增加( = 0.0001)。相反,在3.96±0.47千米·小时时,PCI为3.81±0.88%(高变异性),在SS(4.94±0.58千米·小时)时为2.64±0.75%(低变异性),在5.94±0.70千米·小时时为3.36±1.09%(高变异性)( = 0.001)。这些结果表明,虽然代谢需求和运动学变量随速度增加呈线性变化,但在SS时观察到最有效的GV。因此,SS可能是一种新的方法,用于选择个体步行速度、标准化速度强度并避免步态模式改变。